**Archived** Epic is a high performance statistical parser written in Scala, along with a framework for building complex structured prediction models.
Home Page: http://scalanlp.org/
License: Apache License 2.0
Could you guys please publish epic-parser-en-span for 2.12 ?
Thanks!
I upgraded a project I had to use Epic 0.3 and the most recent taggers and parsers. I'm getting a pretty nasty error here:
[info] java.io.InvalidClassException: breeze.linalg.Counter2$$anon$1; local class incompatible: stream classdesc serialVersionUID = -8653601685403516672, local class serialVersionUID = 6118148492784004600
...
[info] at epic.models.PosTagSelector$.loadTagger(PosTagModelLoader.scala:13)
(full stacktrace below)
It looks like there's a problem in breeze.lingalg.Counter. Did the API possibly change between this upgrade? Perhaps it's related to the fact that I'm using Spark as well as Epic in my project? Here are all of my dependencies
"org.scalanlp" %% "epic" % "0.3",
"org.scalanlp" %% "epic-parser-en-span" % "2015.1.25",
"org.scalanlp" %% "epic-ner-en-conll" % "2015.1.25",
"org.scalanlp" %% "epic-pos-en" % "2015.1.25",
"org.apache.spark" % "spark-core_2.10" % "1.3.0",
"org.apache.spark" % "spark-mllib_2.10" % "1.3.0",
Stacktrace:
[info] java.io.InvalidClassException: breeze.linalg.Counter2$$anon$1; local class incompatible: stream classdesc serialVersionUID = -8653601685403516672, local class serialVersionUID = 6118148492784004600
[info] at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:621)
[info] at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1623)
[info] at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.readArray(ObjectInputStream.java:1707)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1345)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
[info] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
[info] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
[info] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
[info] at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
[info] at epic.models.ClassPathModelLoader.load(ModelLoader.scala:23)
[info] at epic.models.DelegatingLoader.load(ModelLoader.scala:33)
[info] at epic.models.PosTagSelector$.loadTagger(PosTagModelLoader.scala:13)
involves using the parser to split up spans, then using the split spans to make a decision
Hi - could you please check the below Readme extracts
val tagger = epic.models.deserialize[CRF[AnnotatedLabel, String]]("lib/epic-ner-en-conll_2.10-2014.6.3-SNAPSHOT.jar")
val segments = tagger(sentence)
println(tags.render(tagger.outsideLabel))
Gives a compile error "epic.sequences.CRF[epic.trees.AnnotatedLabel,String] does not take parameters"
I tried updating this slightly to the below,
val tagger = epic.models.deserialize[SemiCRF[AnnotatedLabel, String]](("lib/epic-ner-en-conll_2.10-2014.6.3-SNAPSHOT.jar"))
val sentenceSplitter = MLSentenceSegmenter.bundled().get
val tokenizer = new epic.preprocess.TreebankTokenizer()
val sentences: IndexedSeq[IndexedSeq[String]] = sentenceSplitter(input).map(tokenizer(_))
var result = ""
sentences.map{
sentence =>
val tags = tagger.bestSequence(sentence)
result = tags.render(tagger.outsideSymbol)
}
result
Compiles and runs - but doesn't give very interesting output
Thanks,
Brent
My project depends on both epic and breeze (because they're both awesome!)
Unfortunately, in the process of upgrading to breeze 0.12 (we also depend on MLlib which depends on breeze 0.12 as of recent versions of spark) our code broke because the current English POS model:
"org.scalanlp" %% "epic-pos-en" % "2015.2.19"
Depends on breeze 0.11-M0.
If my project depends on both breeze 0.12 and this model, when I go to load the model I get the following:
scala> val model: SemiCRF[Any, String] = epic.models.NerSelector.loadNer("en").get
java.lang.ClassCastException: cannot assign instance of epic.lexicon.SimpleLexicon$SerializedForm to field epic.constraints.LabeledSpanConstraints$LayeredTagConstraintsFactory.lexicon of type epic.constraints.TagConstraints$Factory in instance of epic.constraints.LabeledSpanConstraints$LayeredTagConstraintsFactory
at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2083)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1261)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1995)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1913)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1989)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1913)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1796)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1348)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
at epic.models.ClassPathModelLoader.load(ModelLoader.scala:23)
at epic.models.DelegatingLoader.load(ModelLoader.scala:33)
at epic.models.NerSelector$.loadNer(NerModelLoader.scala:12)
at .<init>(<console>:8)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:734)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:983)
at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:604)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:568)
at scala.tools.nsc.interpreter.ILoop.reallyInterpret$1(ILoop.scala:760)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:805)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:717)
at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581)
at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:882)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:837)
at scala.tools.nsc.interpreter.ILoop.main(ILoop.scala:904)
at xsbt.ConsoleInterface.run(ConsoleInterface.scala:62)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at sbt.compiler.AnalyzingCompiler.call(AnalyzingCompiler.scala:101)
at sbt.compiler.AnalyzingCompiler.console(AnalyzingCompiler.scala:76)
at sbt.Console.sbt$Console$$console0$1(Console.scala:22)
at sbt.Console$$anonfun$apply$2$$anonfun$apply$1.apply$mcV$sp(Console.scala:23)
at sbt.Console$$anonfun$apply$2$$anonfun$apply$1.apply(Console.scala:23)
at sbt.Console$$anonfun$apply$2$$anonfun$apply$1.apply(Console.scala:23)
at sbt.Logger$$anon$4.apply(Logger.scala:85)
at sbt.TrapExit$App.run(TrapExit.scala:248)
at java.lang.Thread.run(Thread.java:724)
I'm not sure what the best way forward is here. I can envision:
Hi,
that would be nice to change all String in CRFModel to W type, it requires string when you want make a CRF.
Am I right?
If you have time, please make the epic-pos-en model available. I have the Treebank data, but it would be easier to not build it myself (and other people might use it if it were available).
Both scala 2.10 and 2.11
1
val sentences: IndexedSeq[IndexedSeq[String]] = sentenceSplitter(text).map(tokenizer).toIndexedSeq
Should be
val sentences: IndexedSeq[IndexedSeq[String]] = sentenceSplitter(text).map(tokenizer(_)).toIndexedSeq
2
loadTaqgger returns an Option, needs for to access
epic.models.PosTagSelector.loadTagger("en")
3
tagger.sentence)
Should be
tagger.bestSequence(sentence)
I tried to retrain the parser on CTB by converting original .fid files to .mrg files and adding the parameter --treebank.treebankType chinese, but it failed and here is the error message.
$ java -Xmx47g -cp path/to/assembly.jar epic.parser.models.NeuralParserTrainer --cache.path constraints.cache --opt.useStochastic -treebank.path path/to/ctb/ --treebank.treebankType chinese --evalOnTest --includeDevInTrain --trainer.modelFactory.annotator epic.trees.annotations.PipelineAnnotator --ann.0 epic.trees.annotations.FilterAnnotations --ann.1 epic.trees.annotations.ForgetHeadTag --ann.2 epic.trees.annotations.Markovize --ann.2.horizontal 0 --ann.2.vertical 0 --modelFactory epic.parser.models.PositionalNeuralModelFactory --threads 8
[main] INFO epic.parser.models.NeuralParserTrainer$ - Training Parser...
Exception in thread "main" java.lang.RuntimeException: error while indexingBinaryRule(@QP[^DP],QP[^QP],CC[^QP]) to BinaryRule(@QP,QP,CC)0
at epic.parser.projections.ProjectionIndexer$$anonfun$apply$5.apply(ProjectionIndexer.scala:114)
at epic.parser.projections.ProjectionIndexer$$anonfun$apply$5.apply(ProjectionIndexer.scala:110)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at epic.parser.projections.ProjectionIndexer$.apply(ProjectionIndexer.scala:110)
at epic.parser.projections.GrammarRefinements$.apply(GrammarRefinements.scala:177)
at epic.parser.GenerativeParser$.annotated(GenerativeParser.scala:124)
at epic.parser.GenerativeParser$.annotatedParser(GenerativeParser.scala:107)
at epic.parser.models.NeuralParserTrainer$.trainParser(NeuralParserTrainer.scala:91)
at epic.parser.models.NeuralParserTrainer$.trainParser(NeuralParserTrainer.scala:35)
at epic.parser.ParserPipeline$class.trainParser(ParserPipeline.scala:92)
at epic.parser.models.NeuralParserTrainer$.trainParser(NeuralParserTrainer.scala:35)
at epic.parser.ParserPipeline$class.main(ParserPipeline.scala:107)
at epic.parser.models.NeuralParserTrainer$.main(NeuralParserTrainer.scala:35)
at epic.parser.models.NeuralParserTrainer.main(NeuralParserTrainer.scala)
So could you help me to find where the mistake is? Thanks a lot!
Hi, there are two errors occurred when I tried to build epic.
Is there any possible way that I can fix it?
Hello, I had just cloned the master branch and tried to build epic just as README instructions: sbt assembly
Then I've got the following error:
module not found: org.scalanlp#sbt-jflex_2.10_0.13;0.1-SNAPSHOT
...
org.scalanlp:sbt-jflex_2.10_0.13:0.1-SNAPSHOT (sbtVersion=0.13, scalaVersion=2.10)
Since I'm also not being able to use any of the epic versions published to https://oss.sonatype.org/content/repositories/snapshots/org/scalanlp/ (because they miss breezer 0.8-SNAPSHOT, and sbt just cant find that), I'm willing to build it from sources, but as you can see it is not being possible.
Hi, I tried to build using different versions of Scala and sbt both, but no luck. Please help.
Hi i just wanted to know if you are production ready ?
How do you compare or related to Core-NLP?
I need to Library to do POS Tagging both in english and spanish. I need extract noun or compound non in document.
[main] INFO epic.parser.models.ParserTrainer$ - Training Parser...
Exception in thread "main" java.lang.NullPointerException
at scala.collection.mutable.ArrayOps$ofRef$.length$extension(ArrayOps.scala:192)
at scala.collection.mutable.ArrayOps$ofRef.length(ArrayOps.scala:192)
at scala.collection.IndexedSeqLike$class.iterator(IndexedSeqLike.scala:90)
at scala.collection.mutable.ArrayOps$ofRef.iterator(ArrayOps.scala:186)
at epic.trees.Treebank$$anon$2.treesFromSection(Treebank.scala:125)
at epic.trees.Treebank$$anonfun$treesFromSections$1.apply(Treebank.scala:67)
at epic.trees.Treebank$$anonfun$treesFromSections$1.apply(Treebank.scala:67)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$21.hasNext(Iterator.scala:836)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.immutable.VectorBuilder.$plus$plus$eq(Vector.scala:732)
at scala.collection.immutable.VectorBuilder.$plus$plus$eq(Vector.scala:708)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toIndexedSeq(TraversableOnce.scala:300)
at scala.collection.AbstractIterator.toIndexedSeq(Iterator.scala:1336)
at epic.trees.ProcessedTreebank.transformTrees(ProcessedTreebank.scala:84)
at epic.trees.ProcessedTreebank.devTrees$lzycompute(ProcessedTreebank.scala:73)
at epic.trees.ProcessedTreebank.devTrees(ProcessedTreebank.scala:73)
at epic.parser.ParserPipeline$class.trainParser(ParserPipeline.scala:88)
at epic.parser.models.ParserTrainer$.trainParser(ParserTrainer.scala:47)
at epic.parser.ParserPipeline$class.main(ParserPipeline.scala:107)
at epic.parser.models.ParserTrainer$.main(ParserTrainer.scala:47)
at epic.parser.models.ParserTrainer.main(ParserTrainer.scala)
https://github.com/dlwh/epic/blob/master/src/main/scala/epic/preprocess/TreebankTokenizer.scala#L52
case "“" => inOpenQuote = true; output += "``"
...
case "”" => inOpenQuote = false; output += "``"
Should that be a +="''" for the curly close quote?
Thanks for Epic!
Hiyas, I'd like to create a PR for packaging and wanted to see if it would be accepted before spending time on it. I'm still stuck on e0238ce given epic-parser-en-span_2.11/2015.2.19 being incompatible with anything newer, so I could just as easily make the changes I need locally and remain forked.
What I'm after at the minimum is to create two modules, one for "core" and one for "tools". Goal here is to get Tika out of the core dependencies, used only in epic.preprocess.TextExtractor, which is really a command-line tool. I don't know how many other tools there are like this or what other effects it might have on the dependency closure, but I think it will be significant.
The reason I am even doing that is Tika depends on Apache POI and a kitchen sink of other detritus. POI has a split-package problem. Once everything is cleaned up, I should at least be able to make the core module into an OSGi bundle.
I just cloned Epic and went to try and run "sbt assembly" and got the following error message:
error sbt.ResolveException: unresolved dependency: org.scalanlp#breeze_2.11;0.12-SNAPSHOT: not found
So I went ahead and installed Breeze just fine and reran in the Epic install, but still got the same error. Suggetions?
Dear dlwh,
Thank you so much for publishing epic!
I have trained a new parsing model using the following command:
"java -cp target/scala-2.11/epic-assembly-0.3.jar epic.parser.models.ParserTrainer
--treebankType simple
--treebank.path "src/main/resources/smallbank"
--modelFactory epic.parser.models.SpanModelFactory
--cache.path constraints.cache
--opt.useStochastic true
--opt.regularization 1.0"
The result after training is as follows:
Could you please let me know where I can find the parsing model?
Quy Nguyen
@dlwh @gregdurrett It seems like something is wrong with en-sent-segmenter.model.ser.gz.
I use epic 0.4.2. In my project MLSentenceSegmenter.bundled() returns MLSentenceSegmenter with inf field as null.
I'm on JDK 1.8
Hi,
I tried to use Epic model in my project, I have a problem with the sbt dependencies. The following is the error I got:
"unresolved dependency: org.scala-sbt#sbt;0.13.1: not found"
Here is the code I use that can reproduce the error.
https://github.com/jiangss/epic-example
Please advise.
Thanks!
build.sbt:
...
libraryDependencies += "org.scalanlp" %% "epic" % "0.4.3"
libraryDependencies += "org.scalanlp" %% "epic-pos-en" % "2017.3.10"
...
code snippet:
...
val tagger = epic.models.PosTagSelector.loadTagger("en").get
val titleTags = tagger.bestSequence(titleSentence)
...
titleSentence is a Vector of strings containing the string "1stgeneration"
When I try to tag the string "1stgeneration", my application fails with the error below (which is rather incomprehensible to me). Is this a bug or can anyone help me fix this? My own research led to nothing.
[error] (run-main-0) java.lang.AssertionError: assertion failed: Vector(WordFeature(-LC-NUM-ion,'Class)) Index(IndicatorFeature(In),IndicatorFeature(an),IndicatorFeature(Oct.),WordFeature(-LC-NUM,'Class),WordFeature(-LC,'Class),IndicatorFeature(of),IndicatorFeature(``),IndicatorFeature(The),WordFeature(-INITC,'Class),IndicatorFeature(''),IndicatorFeature(at),IndicatorFeature(Chicago),IndicatorFeature('s),IndicatorFeature((),WordFeature(-INITC-ed,'Class),WordFeature(-INITC-s,'Class),IndicatorFeature(the),IndicatorFeature(in),WordFeature(-INITC-y,'Class),IndicatorFeature(City),IndicatorFeature(,),IndicatorFeature(&),IndicatorFeature()),IndicatorFeature(role),WordFeature(-LC-ed,'Class),IndicatorFeature(by),IndicatorFeature(was),WordFeature(-LC-ly,'Class),IndicatorFeature(to),IndicatorFeature(.),IndicatorFeature(Ms.),WordFeature(-LC-s,'Class),WordFeature(-CAPS-DASH,'Class),IndicatorFeature(Inc.),IndicatorFeature(said),IndicatorFeature(it),IndicatorFeature(expects),IndicatorFeature(its),IndicatorFeature(U.S.),IndicatorFeature(sales),IndicatorFeature(remain),WordFeature(-LC-y,'Class),IndicatorFeature(about),IndicatorFeature(cars),IndicatorFeature(1990),IndicatorFeature(auto),IndicatorFeature(maker),IndicatorFeature(last),IndicatorFeature(year),IndicatorFeature(sold),WordFeature(-INITC-er,'Class),IndicatorFeature(president),IndicatorFeature(and),IndicatorFeature(chief),IndicatorFeature(executive),IndicatorFeature(officer),IndicatorFeature(he),IndicatorFeature(growth),IndicatorFeature(for),IndicatorFeature(Britain),IndicatorFeature(Europe),IndicatorFeature(Eastern),IndicatorFeature(markets),WordFeature(-CAPS,'Class),WordFeature(-CAPS-s,'Class),IndicatorFeature(increased),IndicatorFeature(10),IndicatorFeature(cents),IndicatorFeature(from),IndicatorFeature(seven),IndicatorFeature(a),IndicatorFeature(share),IndicatorFeature(new),IndicatorFeature(rate),IndicatorFeature(will),IndicatorFeature(be),IndicatorFeature(15),IndicatorFeature(A),IndicatorFeature(record),IndicatorFeature(has),IndicatorFeature(n't),IndicatorFeature(been),IndicatorFeature(set),IndicatorFeature(based),IndicatorFeature(Los),IndicatorFeature(Angeles),IndicatorFeature(makes),IndicatorFeature(computer),IndicatorFeature(building),IndicatorFeature(products),IndicatorFeature(Investors),IndicatorFeature(are),WordFeature(-LC-ing,'Class),IndicatorFeature(Securities),IndicatorFeature(Exchange),IndicatorFeature(Commission),IndicatorFeature(not),IndicatorFeature(their),IndicatorFeature(information),IndicatorFeature(stock),IndicatorFeature(corporate),IndicatorFeature(proposal),IndicatorFeature(some),IndicatorFeature(company),IndicatorFeature(executives),IndicatorFeature(would),IndicatorFeature(on),WordFeature(-LC-er,'Class),IndicatorFeature(as),WordFeature(-LC-DASH,'Class),IndicatorFeature(individual),IndicatorFeature(investors),WordFeature(-LC-al,'Class),IndicatorFeature(money),IndicatorFeature(managers),IndicatorFeature(They),IndicatorFeature(make),IndicatorFeature(agency),IndicatorFeature(changes),IndicatorFeature(proposed),IndicatorFeature(this),IndicatorFeature(past),IndicatorFeature(that),IndicatorFeature(among),IndicatorFeature(other),IndicatorFeature(things),IndicatorFeature(many),IndicatorFeature(own),IndicatorFeature(companies),IndicatorFeature('),IndicatorFeature(shares),IndicatorFeature(also),IndicatorFeature(allow),IndicatorFeature(report),IndicatorFeature(options),IndicatorFeature(later),IndicatorFeature(less),IndicatorFeature(often),IndicatorFeature(Many),IndicatorFeature(investor),IndicatorFeature(so),IndicatorFeature(1987),IndicatorFeature(market),IndicatorFeature(--),IndicatorFeature(already),IndicatorFeature(against),IndicatorFeature(little),IndicatorFeature(any),IndicatorFeature(might),IndicatorFeature(get),IndicatorFeature(out),IndicatorFeature(stocks),IndicatorFeature(paid),IndicatorFeature(level),IndicatorFeature(one),IndicatorFeature(received),IndicatorFeature(since),IndicatorFeature(were),IndicatorFeature(17),WordFeature(-INITC-ly,'Class),WordFeature(-LC-ion,'Class),IndicatorFeature(did),IndicatorFeature(really),IndicatorFeature(believe),IndicatorFeature(rules),IndicatorFeature(force),IndicatorFeature(directors),IndicatorFeature(within),IndicatorFeature(month),IndicatorFeature(after),IndicatorFeature(transaction),IndicatorFeature(But),IndicatorFeature(25),IndicatorFeature(%),IndicatorFeature(according),IndicatorFeature(figures),IndicatorFeature(reports),IndicatorFeature(late),IndicatorFeature(effort),IndicatorFeature(federal),IndicatorFeature(boost),IndicatorFeature(who),IndicatorFeature(special),IndicatorFeature(office),IndicatorFeature(policy),IndicatorFeature(which),IndicatorFeature(officials),IndicatorFeature(had),IndicatorFeature(until),IndicatorFeature(today),IndicatorFeature(comment),IndicatorFeature(issue),IndicatorFeature(more),IndicatorFeature(than),IndicatorFeature(almost),IndicatorFeature(Mr.),IndicatorFeature(probably),IndicatorFeature(vote),IndicatorFeature(early),IndicatorFeature(next),IndicatorFeature(all),IndicatorFeature(those),IndicatorFeature(Committee),IndicatorFeature(Federal),WordFeature(-INITC-ion,'Class),IndicatorFeature(American),IndicatorFeature(Association),IndicatorFeature(example),IndicatorFeature({),IndicatorFeature(law),IndicatorFeature(}),IndicatorFeature(business),IndicatorFeature(What),IndicatorFeature(most),IndicatorFeature(is),IndicatorFeature(effect),IndicatorFeature(they),IndicatorFeature(say),IndicatorFeature(have),WordFeature(-LC-ity,'Class),IndicatorFeature(trading),IndicatorFeature(activity),IndicatorFeature(buying),IndicatorFeature(or),IndicatorFeature(selling),IndicatorFeature(director),IndicatorFeature(short),IndicatorFeature(period),IndicatorFeature(time),WordFeature(-INITC-ing,'Class),IndicatorFeature(estimates),IndicatorFeature(cut),IndicatorFeature(third),IndicatorFeature(such),IndicatorFeature(marketing),IndicatorFeature(finance),IndicatorFeature(research),IndicatorFeature(development),IndicatorFeature(still),IndicatorFeature(required),IndicatorFeature(annual),IndicatorFeature(under),IndicatorFeature(least),IndicatorFeature(if),IndicatorFeature(following),IndicatorFeature(Robert),IndicatorFeature(North),IndicatorFeature(data),IndicatorFeature(key),IndicatorFeature(may),IndicatorFeature(while),IndicatorFeature(them),IndicatorFeature(when),IndicatorFeature(do),IndicatorFeature(want),IndicatorFeature(change),IndicatorFeature(should),IndicatorFeature(Congress),IndicatorFeature(added),IndicatorFeature(likely),IndicatorFeature(legislation),IndicatorFeature(basis),IndicatorFeature(nation),IndicatorFeature(largest),IndicatorFeature(fund),IndicatorFeature($),IndicatorFeature(billion),IndicatorFeature(employees),IndicatorFeature(plans),IndicatorFeature(offer),IndicatorFeature(two),IndicatorFeature(investment),IndicatorFeature(million),WordFeature(-INITC-ity,'Class),IndicatorFeature(bond),WordFeature(-LC-est,'Class),IndicatorFeature(Both),IndicatorFeature(funds),IndicatorFeature(expected),IndicatorFeature(begin),IndicatorFeature(around),IndicatorFeature(March),IndicatorFeature(1),IndicatorFeature(subject),IndicatorFeature(approval),IndicatorFeature(For),IndicatorFeature(up),IndicatorFeature(must),IndicatorFeature(plan),IndicatorFeature(Some),IndicatorFeature(institutions),IndicatorFeature(part),IndicatorFeature(agreement),IndicatorFeature(pressure),IndicatorFeature(provide),IndicatorFeature(reached),IndicatorFeature(with),IndicatorFeature(December),IndicatorFeature(securities),IndicatorFeature(South),IndicatorFeature(power),IndicatorFeature(cases),IndicatorFeature(investments),IndicatorFeature(significant),IndicatorFeature(going),IndicatorFeature(into),IndicatorFeature(bonds),IndicatorFeature(including),IndicatorFeature(much),IndicatorFeature(foreign),IndicatorFeature(buy),IndicatorFeature(sell),IndicatorFeature(futures),IndicatorFeature(contracts),IndicatorFeature(New),IndicatorFeature(York),IndicatorFeature(State),IndicatorFeature(Department),IndicatorFeature(Under),IndicatorFeature(able),IndicatorFeature(receive),IndicatorFeature(cash),IndicatorFeature(offered),IndicatorFeature(currently),IndicatorFeature(limited),IndicatorFeature(Co.),IndicatorFeature(equipment),IndicatorFeature(shareholders),IndicatorFeature(right),IndicatorFeature(purchase),IndicatorFeature(half),IndicatorFeature(price),IndicatorFeature(certain),IndicatorFeature(takeover),IndicatorFeature(years),IndicatorFeature(old),IndicatorFeature(senior),IndicatorFeature(vice),IndicatorFeature(concern),IndicatorFeature(technology),IndicatorFeature(group),IndicatorFeature(position),IndicatorFeature(work),IndicatorFeature(lot),IndicatorFeature(because),IndicatorFeature(taken),IndicatorFeature(hard),IndicatorFeature(line),IndicatorFeature(problem),IndicatorFeature(:),IndicatorFeature(He),IndicatorFeature(does),IndicatorFeature(same),IndicatorFeature(over),IndicatorFeature(again),IndicatorFeature(Richard),IndicatorFeature(ago),IndicatorFeature(very),IndicatorFeature(like),IndicatorFeature(dropped),IndicatorFeature(though),IndicatorFeature(now),IndicatorFeature(show),IndicatorFeature(few),IndicatorFeature(thing),WordFeature(-INITC-DASH,'Class),IndicatorFeature(you),IndicatorFeature(ca),IndicatorFeature(his),IndicatorFeature(commercial),IndicatorFeature(what),IndicatorFeature(His),IndicatorFeature(recent),WordFeature(-INITC-al,'Class),IndicatorFeature(case),IndicatorFeature(point),IndicatorFeature(It),IndicatorFeature(black),IndicatorFeature(suit),IndicatorFeature(announced),IndicatorFeature(just),IndicatorFeature(family),IndicatorFeature(her),WordFeature(-CAPS-DASH-s,'Class),IndicatorFeature(no),IndicatorFeature(could),IndicatorFeature(well),IndicatorFeature(second),IndicatorFeature(And),IndicatorFeature(went),IndicatorFeature(through),IndicatorFeature(first),IndicatorFeature(longer),IndicatorFeature(five),IndicatorFeature(An),IndicatorFeature(beginning),IndicatorFeature(lead),IndicatorFeature(high),IndicatorFeature(off),IndicatorFeature(Air),IndicatorFeature(him),IndicatorFeature(great),IndicatorFeature(then),IndicatorFeature(way),IndicatorFeature(end),IndicatorFeature(however),IndicatorFeature(ever),IndicatorFeature(but),IndicatorFeature(too),IndicatorFeature(away),IndicatorFeature(That),IndicatorFeature(before),IndicatorFeature(during),IndicatorFeature(?),IndicatorFeature(take),IndicatorFeature(us),IndicatorFeature(11),IndicatorFeature(1\/2),IndicatorFeature(without),IndicatorFeature(having),IndicatorFeature(future),IndicatorFeature(can),IndicatorFeature(only),IndicatorFeature(performance),IndicatorFeature(One),IndicatorFeature(President),IndicatorFeature(international),IndicatorFeature(fact),IndicatorFeature(world),IndicatorFeature(This),IndicatorFeature(members),IndicatorFeature(United),IndicatorFeature(Now),IndicatorFeature(Bush),IndicatorFeature(decision),IndicatorFeature(we),IndicatorFeature(think),IndicatorFeature(along),IndicatorFeature(left),IndicatorFeature(financial),IndicatorFeature(top),IndicatorFeature(got),IndicatorFeature(personal),IndicatorFeature(several),IndicatorFeature(plants),IndicatorFeature(France),IndicatorFeature(sent),IndicatorFeature(even),IndicatorFeature(projects),IndicatorFeature(continue),IndicatorFeature(International),IndicatorFeature(means),IndicatorFeature(West),IndicatorFeature(pay),IndicatorFeature(World),IndicatorFeature(give),IndicatorFeature(government),IndicatorFeature(rights),IndicatorFeature(;),IndicatorFeature(held),IndicatorFeature(support),IndicatorFeature(impact),IndicatorFeature(Soviet),IndicatorFeature(holding),IndicatorFeature(seems),IndicatorFeature(current),IndicatorFeature(public),IndicatorFeature(charge),IndicatorFeature(programs),IndicatorFeature(former),IndicatorFeature(head),IndicatorFeature(military),WordFeature(-LC-DASH-s,'Class),IndicatorFeature(division),IndicatorFeature(staff),IndicatorFeature(working),IndicatorFeature(once),IndicatorFeature(budget),IndicatorFeature(changed),IndicatorFeature(John),IndicatorFeature(state),IndicatorFeature(told),IndicatorFeature(soon),IndicatorFeature(week),IndicatorFeature(raise),WordFeature(-LC-NUM-DASH,'Class),IndicatorFeature(French),IndicatorFeature(owns),IndicatorFeature(Other),IndicatorFeature(countries),IndicatorFeature(Germany),IndicatorFeature(continued),IndicatorFeature(We),IndicatorFeature(see),IndicatorFeature(free),IndicatorFeature(course),IndicatorFeature(made),IndicatorFeature(largely),IndicatorFeature(these),IndicatorFeature(home),IndicatorFeature(times),IndicatorFeature(there),IndicatorFeature(reason),IndicatorFeature(Western),IndicatorFeature(Systems),IndicatorFeature(number),IndicatorFeature(plant),IndicatorFeature(production),IndicatorFeature(itself),IndicatorFeature(another),IndicatorFeature(known),IndicatorFeature(similar),IndicatorFeature(seen),IndicatorFeature(especially),IndicatorFeature(subsidiary),IndicatorFeature(producers),IndicatorFeature(On),IndicatorFeature(process),IndicatorFeature(each),IndicatorFeature(making),IndicatorFeature(using),WordFeature(-LC-NUM-s,'Class),IndicatorFeature(20),IndicatorFeature(majority),IndicatorFeature(difficult),IndicatorFeature(China),IndicatorFeature(workers),IndicatorFeature(country),IndicatorFeature(At),IndicatorFeature(major),IndicatorFeature(Canada),IndicatorFeature(University),IndicatorFeature(California),IndicatorFeature(every),IndicatorFeature(hurt),IndicatorFeature(order),IndicatorFeature(large),IndicatorFeature(enough),IndicatorFeature(produce),IndicatorFeature(yield),IndicatorFeature(30),IndicatorFeature(used),IndicatorFeature(include),IndicatorFeature(need),IndicatorFeature(costs),IndicatorFeature(demand),IndicatorFeature(Co),IndicatorFeature(problems),IndicatorFeature(However),IndicatorFeature(Paul),IndicatorFeature(Corp.),IndicatorFeature(Calif.),IndicatorFeature(called),IndicatorFeature(remains),IndicatorFeature(active),IndicatorFeature(days),IndicatorFeature(rather),IndicatorFeature(There),IndicatorFeature(acquire),IndicatorFeature(try),IndicatorFeature(between),IndicatorFeature(Bank),IndicatorFeature(Japan),IndicatorFeature('re),IndicatorFeature(being),IndicatorFeature(latest),IndicatorFeature(50),IndicatorFeature(Japanese),IndicatorFeature(banks),IndicatorFeature(led),IndicatorFeature(help),IndicatorFeature(loans),IndicatorFeature(bank),IndicatorFeature(owned),IndicatorFeature(put),IndicatorFeature(financing),IndicatorFeature(biggest),IndicatorFeature(far),IndicatorFeature(domestic),IndicatorFeature(issues),IndicatorFeature(3),IndicatorFeature(dollars),IndicatorFeature(4),IndicatorFeature(come),IndicatorFeature(fiscal),IndicatorFeature(June),IndicatorFeature(With),IndicatorFeature(here),IndicatorFeature(David),IndicatorFeature(Tuesday),IndicatorFeature(Ltd.),IndicatorFeature(National),IndicatorFeature(I),IndicatorFeature(interests),IndicatorFeature(banking),IndicatorFeature(lower),IndicatorFeature(months),IndicatorFeature(Meanwhile),IndicatorFeature(smaller),IndicatorFeature(seeking),IndicatorFeature(open),IndicatorFeature(full),IndicatorFeature(competition),IndicatorFeature(capital),IndicatorFeature(run),IndicatorFeature(both),IndicatorFeature(businesses),IndicatorFeature(started),IndicatorFeature(venture),IndicatorFeature(use),IndicatorFeature(accounts),IndicatorFeature(account),IndicatorFeature(London),IndicatorFeature(move),IndicatorFeature(brokerage),IndicatorFeature(firms),IndicatorFeature(simply),IndicatorFeature(reported),IndicatorFeature(third-quarter),IndicatorFeature(earnings),IndicatorFeature(yesterday),IndicatorFeature(average),IndicatorFeature(analysts),IndicatorFeature(higher),IndicatorFeature(named),IndicatorFeature(industrial),IndicatorFeature(systems),IndicatorFeature(A.),IndicatorFeature(Monday),IndicatorFeature(equity),IndicatorFeature(As),IndicatorFeature(manager),IndicatorFeature(different),IndicatorFeature(four),IndicatorFeature(Series),IndicatorFeature(says),IndicatorFeature(long),IndicatorFeature(good),IndicatorFeature(television),IndicatorFeature(contract),IndicatorFeature(near),IndicatorFeature(down),IndicatorFeature(involved),IndicatorFeature(always),IndicatorFeature(You),IndicatorFeature(hit),IndicatorFeature(lawyers),IndicatorFeature(real),IndicatorFeature(estate),IndicatorFeature(better),IndicatorFeature(never),IndicatorFeature(car),IndicatorFeature(six),IndicatorFeature(James),IndicatorFeature(When),IndicatorFeature(offering),IndicatorFeature(available),IndicatorFeature(life),IndicatorFeature(back),IndicatorFeature(clear),IndicatorFeature(themselves),IndicatorFeature(something),IndicatorFeature(close),IndicatorFeature(Washington),IndicatorFeature(claims),IndicatorFeature(insurance),IndicatorFeature(Texas),IndicatorFeature(team),IndicatorFeature(me),IndicatorFeature(White),WordFeature(-CAPS-y,'Class),IndicatorFeature(Big),IndicatorFeature(These),IndicatorFeature(While),IndicatorFeature(getting),IndicatorFeature(man),IndicatorFeature(magazine),IndicatorFeature(people),IndicatorFeature(Most),IndicatorFeature(others),IndicatorFeature(recently),IndicatorFeature('m),IndicatorFeature(look),IndicatorFeature(whether),IndicatorFeature(So),IndicatorFeature(base),IndicatorFeature(Still),IndicatorFeature(how),IndicatorFeature(expect),IndicatorFeature(three),IndicatorFeature(Even),IndicatorFeature(If),IndicatorFeature(know),IndicatorFeature(wo),IndicatorFeature(lost),IndicatorFeature(become),IndicatorFeature(control),IndicatorFeature(keep),IndicatorFeature(After),IndicatorFeature(disclosed),IndicatorFeature(operations),IndicatorFeature(local),IndicatorFeature(service),IndicatorFeature(states),IndicatorFeature(build),IndicatorFeature(gas),IndicatorFeature(acquisition),IndicatorFeature(April),IndicatorFeature(completed),IndicatorFeature(common),IndicatorFeature(outstanding),IndicatorFeature(assets),IndicatorFeature(department),IndicatorFeature(Nov.),IndicatorFeature(previously),IndicatorFeature(operating),IndicatorFeature(retail),IndicatorFeature(Bay),IndicatorFeature(October),IndicatorFeature(31),IndicatorFeature(1989),IndicatorFeature(interest),IndicatorFeature(rates),IndicatorFeature(below),IndicatorFeature(general),IndicatorFeature(levels),WordFeature(-CAPS-al,'Class),IndicatorFeature(9),IndicatorFeature(8),IndicatorFeature(low),IndicatorFeature(7\/8),IndicatorFeature(bid),IndicatorFeature(traded),IndicatorFeature(Inc),IndicatorFeature(7),IndicatorFeature(3\/4),IndicatorFeature(brokers),IndicatorFeature(exchange),WordFeature(-CAPS-er,'Class),IndicatorFeature(General),IndicatorFeature(60),IndicatorFeature(150),IndicatorFeature(notes),IndicatorFeature(dealers),IndicatorFeature(Average),IndicatorFeature(unit),IndicatorFeature(credit),IndicatorFeature(5\/8),IndicatorFeature(3\/8),WordFeature(-CAPS-ed,'Class),IndicatorFeature(dollar),IndicatorFeature(auction),IndicatorFeature(bills),IndicatorFeature(face),IndicatorFeature(value),IndicatorFeature(units),IndicatorFeature(13),IndicatorFeature(weeks),IndicatorFeature(mortgage),IndicatorFeature(2),WordFeature(-CAPS-ion,'Class),IndicatorFeature(priced),IndicatorFeature(return),IndicatorFeature(returns),IndicatorFeature(product),IndicatorFeature(rose),IndicatorFeature(August),IndicatorFeature(result),IndicatorFeature(year-earlier),IndicatorFeature(total),IndicatorFeature(goods),IndicatorFeature(services),IndicatorFeature(July),IndicatorFeature(index),IndicatorFeature(September),IndicatorFeature(decline),IndicatorFeature(industry),IndicatorFeature(Dow),IndicatorFeature(Jones),IndicatorFeature(acquired),IndicatorFeature(Financial),IndicatorFeature(loan),IndicatorFeature(losses),IndicatorFeature(construction),IndicatorFeature(caused),IndicatorFeature(previous),IndicatorFeature(sale),IndicatorFeature(asked),IndicatorFeature(British),IndicatorFeature(Jaguar),IndicatorFeature(PLC),IndicatorFeature(House),IndicatorFeature(best),IndicatorFeature(quickly),IndicatorFeature(possible),IndicatorFeature(leading),IndicatorFeature(Ford),IndicatorFeature(trying),IndicatorFeature(GM),IndicatorFeature(joint),IndicatorFeature(stake),IndicatorFeature(action),IndicatorFeature(management),IndicatorFeature(deal),IndicatorFeature(European),IndicatorFeature(analyst),IndicatorFeature(Stock),IndicatorFeature(gain),IndicatorFeature(heavy),IndicatorFeature(volume),IndicatorFeature(closed),IndicatorFeature(Analysts),IndicatorFeature(#),IndicatorFeature(Sept.),IndicatorFeature(independent),IndicatorFeature(wants),IndicatorFeature(huge),IndicatorFeature(Institute),IndicatorFeature(talks),IndicatorFeature(agreed),IndicatorFeature(either),IndicatorFeature(start),IndicatorFeature(statement),IndicatorFeature(board),IndicatorFeature(holders),IndicatorFeature(meeting),IndicatorFeature(noted),IndicatorFeature(call),IndicatorFeature(declined),IndicatorFeature(our),IndicatorFeature(further),IndicatorFeature(Although),IndicatorFeature(yet),IndicatorFeature(long-term),IndicatorFeature(taking),IndicatorFeature(risk),IndicatorFeature(administration),IndicatorFeature(done),IndicatorFeature(economy),IndicatorFeature(Mrs.),IndicatorFeature(America),IndicatorFeature(revenue),IndicatorFeature(William),IndicatorFeature(additional),IndicatorFeature(chairman),IndicatorFeature(parent),IndicatorFeature(due),IndicatorFeature(parts),IndicatorFeature(D.),IndicatorFeature(J.),IndicatorFeature(nine),IndicatorFeature(ended),IndicatorFeature(net),IndicatorFeature(loss),IndicatorFeature(compared),IndicatorFeature(national),IndicatorFeature(Sales),IndicatorFeature(fell),IndicatorFeature(earlier),IndicatorFeature(ahead),IndicatorFeature(12),IndicatorFeature(showed),IndicatorFeature(Tokyo),IndicatorFeature(points),IndicatorFeature(First),IndicatorFeature(estimated),IndicatorFeature(failed),IndicatorFeature(bought),IndicatorFeature(official),IndicatorFeature(profits),IndicatorFeature(despite),IndicatorFeature(political),IndicatorFeature(14),IndicatorFeature(inflation),IndicatorFeature(consumer),IndicatorFeature(prices),IndicatorFeature(economic),IndicatorFeature(oil),IndicatorFeature(although),IndicatorFeature(supply),IndicatorFeature(day),IndicatorFeature(gains),IndicatorFeature(traders),IndicatorFeature(40),IndicatorFeature(gained),IndicatorFeature(turned),IndicatorFeature(news),IndicatorFeature(Friday),IndicatorFeature(yen),IndicatorFeature(Wall),IndicatorFeature(Street),IndicatorFeature(makers),IndicatorFeature(scheduled),IndicatorFeature(currency),IndicatorFeature(helped),IndicatorFeature(health),IndicatorFeature(Hong),IndicatorFeature(Kong),IndicatorFeature(Morgan),IndicatorFeature(Capital),IndicatorFeature(To),IndicatorFeature(100),IndicatorFeature(percentage),IndicatorFeature(food),IndicatorFeature(rise),IndicatorFeature(above),IndicatorFeature(strong),IndicatorFeature(orders),IndicatorFeature(measure),IndicatorFeature(name),IndicatorFeature(5),IndicatorFeature(Board),IndicatorFeature(increase),IndicatorFeature(terms),IndicatorFeature(slightly),IndicatorFeature(Treasury),IndicatorFeature(bill),IndicatorFeature(considered),IndicatorFeature(increases),IndicatorFeature(Among),IndicatorFeature(range),IndicatorFeature(San),IndicatorFeature(Francisco),IndicatorFeature(my),IndicatorFeature(go),IndicatorFeature(kind),IndicatorFeature(500),IndicatorFeature(6),IndicatorFeature(began),IndicatorFeature(came),IndicatorFeature(hold),IndicatorFeature(turn),IndicatorFeature(view),IndicatorFeature(your),IndicatorFeature(coming),IndicatorFeature(doing),IndicatorFeature(whose),WordFeature(-LC-NUM-DASH-s,'Class),IndicatorFeature(where),IndicatorFeature(aid),IndicatorFeature(included),IndicatorFeature(efforts),IndicatorFeature(fall),IndicatorFeature(saying),IndicatorFeature(damage),IndicatorFeature(drop),IndicatorFeature(reduce),IndicatorFeature(Fed),IndicatorFeature(Chairman),IndicatorFeature(Rep.),IndicatorFeature(instead),IndicatorFeature(spokesman),IndicatorFeature(German),IndicatorFeature(trade),IndicatorFeature(firm),IndicatorFeature(Michael),IndicatorFeature(partner),IndicatorFeature(defense),IndicatorFeature(raised),IndicatorFeature(potential),IndicatorFeature(leader),IndicatorFeature(seem),IndicatorFeature(Airlines),IndicatorFeature(1988),IndicatorFeature(nearly),IndicatorFeature(Pacific),IndicatorFeature(area),IndicatorFeature(gold),IndicatorFeature(growing),IndicatorFeature(income),IndicatorFeature(By),IndicatorFeature(results),IndicatorFeature(given),IndicatorFeature(Dec.),IndicatorFeature(quarter),IndicatorFeature(approved),IndicatorFeature(18),IndicatorFeature(airline),IndicatorFeature(network),IndicatorFeature(Drexel),IndicatorFeature(leaders),IndicatorFeature(Senate),IndicatorFeature(program),IndicatorFeature(includes),IndicatorFeature(history),IndicatorFeature(labor),IndicatorFeature(small),IndicatorFeature(meet),IndicatorFeature(job),IndicatorFeature(toward),IndicatorFeature(tax),IndicatorFeature(thought),IndicatorFeature(Industries),WordFeature(-INITC-NUM-DASH,'Class),IndicatorFeature(debt),IndicatorFeature(paper),IndicatorFeature(situation),IndicatorFeature(manufacturing),IndicatorFeature(profit),IndicatorFeature(planned),IndicatorFeature(composite),IndicatorFeature(fourth),IndicatorFeature(particularly),IndicatorFeature(reduced),IndicatorFeature(found),IndicatorFeature(All),IndicatorFeature(Boston),IndicatorFeature(settlement),IndicatorFeature(charges),IndicatorFeature(customers),IndicatorFeature(computers),IndicatorFeature(East),IndicatorFeature(system),IndicatorFeature(1986),IndicatorFeature(lines),IndicatorFeature(legal),IndicatorFeature(took),IndicatorFeature(Corp),WordFeature(-CAPS-NUM,'Class),IndicatorFeature(cost),IndicatorFeature(concerns),IndicatorFeature(she),IndicatorFeature(Last),IndicatorFeature(Group),IndicatorFeature(amount),IndicatorFeature(deficit),IndicatorFeature(issued),IndicatorFeature(Trust),IndicatorFeature(spending),IndicatorFeature(bad),IndicatorFeature(big),IndicatorFeature(question),IndicatorFeature(city),IndicatorFeature('ve),IndicatorFeature(house),IndicatorFeature('ll),IndicatorFeature(attorney),IndicatorFeature(dividend),IndicatorFeature(16),WordFeature(-CAPS-est,'Class),IndicatorFeature(payments),IndicatorFeature(trust),IndicatorFeature(portfolio),IndicatorFeature(note),IndicatorFeature(addition),IndicatorFeature(Judge),IndicatorFeature(judge),IndicatorFeature(steel),IndicatorFeature(court),IndicatorFeature(find),IndicatorFeature(areas),IndicatorFeature(clients),IndicatorFeature(outside),IndicatorFeature(Court),IndicatorFeature(...),IndicatorFeature(hours),IndicatorFeature(filing),IndicatorFeature(filed),IndicatorFeature(Union),IndicatorFeature(earthquake),IndicatorFeature(private),IndicatorFeature(1\/4),IndicatorFeature(S&P),IndicatorFeature(Merrill),IndicatorFeature(Lynch),WordFeature(-INITC-est,'Class),IndicatorFeature(via),IndicatorFeature(200),IndicatorFeature(marks),IndicatorFeature(Revenue),IndicatorFeature(taxes),IndicatorFeature(creditors),IndicatorFeature(Since),IndicatorFeature(strategy),IndicatorFeature(Canadian),IndicatorFeature(property),IndicatorFeature(IBM),IndicatorFeature(Business),IndicatorFeature(place),IndicatorFeature(needed),IndicatorFeature(jumped),IndicatorFeature(project),IndicatorFeature(Warner),IndicatorFeature(CBS),IndicatorFeature(committee),IndicatorFeature(advertising),IndicatorFeature(ad),IndicatorFeature(`),IndicatorFeature(campaign),IndicatorFeature(stores),WordFeature(-CAPS-ing,'Class),WordFeature(-CAPS-NUM-DASH,'Class),IndicatorFeature(pilots),IndicatorFeature(estimate),IndicatorFeature(calls),IndicatorFeature(union),IndicatorFeature(drug),IndicatorFeature(important),IndicatorFeature(adds),IndicatorFeature(eight),WordFeature(-INITC-NUM,'Class),IndicatorFeature(George),IndicatorFeature(groups),IndicatorFeature(conference),IndicatorFeature(looking),IndicatorFeature(TV),IndicatorFeature(quake),IndicatorFeature(posted),IndicatorFeature(related),IndicatorFeature(Sen.),IndicatorFeature(22),IndicatorFeature(Wednesday),IndicatorFeature(reserves),IndicatorFeature(restructuring),IndicatorFeature(buyers),IndicatorFeature(buy-out),IndicatorFeature(Shearson),IndicatorFeature(UAL),IndicatorFeature(francs),IndicatorFeature(1\/8),WordFeature(-INITC-DASH-s,'Class),IndicatorFeature(junk),IndicatorFeature(study),IndicatorFeature(Thursday),IndicatorFeature(abortion),WordFeature(-CAPS-NUM-DASH-s,'Class),IndicatorFeature(Noriega),WordFeature(-CAPS-ly,'Class),WordFeature(-INITC-NUM-DASH-s,'Class),WordFeature(-CAPS-ity,'Class),WordFeature(-INITC-NUM-s,'Class))
[error] java.lang.AssertionError: assertion failed: Vector(WordFeature(-LC-NUM-ion,'Class)) Index(IndicatorFeature(In),IndicatorFeature(an),IndicatorFeature(Oct.),WordFeature(-LC-NUM,'Class),WordFeature(-LC,'Class),IndicatorFeature(of),IndicatorFeature(``),IndicatorFeature(The),WordFeature(-INITC,'Class),IndicatorFeature(''),IndicatorFeature(at),IndicatorFeature(Chicago),IndicatorFeature('s),IndicatorFeature((),WordFeature(-INITC-ed,'Class),WordFeature(-INITC-s,'Class),IndicatorFeature(the),IndicatorFeature(in),WordFeature(-INITC-y,'Class),IndicatorFeature(City),IndicatorFeature(,),IndicatorFeature(&),IndicatorFeature()),IndicatorFeature(role),WordFeature(-LC-ed,'Class),IndicatorFeature(by),IndicatorFeature(was),WordFeature(-LC-ly,'Class),IndicatorFeature(to),IndicatorFeature(.),IndicatorFeature(Ms.),WordFeature(-LC-s,'Class),WordFeature(-CAPS-DASH,'Class),IndicatorFeature(Inc.),IndicatorFeature(said),IndicatorFeature(it),IndicatorFeature(expects),IndicatorFeature(its),IndicatorFeature(U.S.),IndicatorFeature(sales),IndicatorFeature(remain),WordFeature(-LC-y,'Class),IndicatorFeature(about),IndicatorFeature(cars),IndicatorFeature(1990),IndicatorFeature(auto),IndicatorFeature(maker),IndicatorFeature(last),IndicatorFeature(year),IndicatorFeature(sold),WordFeature(-INITC-er,'Class),IndicatorFeature(president),IndicatorFeature(and),IndicatorFeature(chief),IndicatorFeature(executive),IndicatorFeature(officer),IndicatorFeature(he),IndicatorFeature(growth),IndicatorFeature(for),IndicatorFeature(Britain),IndicatorFeature(Europe),IndicatorFeature(Eastern),IndicatorFeature(markets),WordFeature(-CAPS,'Class),WordFeature(-CAPS-s,'Class),IndicatorFeature(increased),IndicatorFeature(10),IndicatorFeature(cents),IndicatorFeature(from),IndicatorFeature(seven),IndicatorFeature(a),IndicatorFeature(share),IndicatorFeature(new),IndicatorFeature(rate),IndicatorFeature(will),IndicatorFeature(be),IndicatorFeature(15),IndicatorFeature(A),IndicatorFeature(record),IndicatorFeature(has),IndicatorFeature(n't),IndicatorFeature(been),IndicatorFeature(set),IndicatorFeature(based),IndicatorFeature(Los),IndicatorFeature(Angeles),IndicatorFeature(makes),IndicatorFeature(computer),IndicatorFeature(building),IndicatorFeature(products),IndicatorFeature(Investors),IndicatorFeature(are),WordFeature(-LC-ing,'Class),IndicatorFeature(Securities),IndicatorFeature(Exchange),IndicatorFeature(Commission),IndicatorFeature(not),IndicatorFeature(their),IndicatorFeature(information),IndicatorFeature(stock),IndicatorFeature(corporate),IndicatorFeature(proposal),IndicatorFeature(some),IndicatorFeature(company),IndicatorFeature(executives),IndicatorFeature(would),IndicatorFeature(on),WordFeature(-LC-er,'Class),IndicatorFeature(as),WordFeature(-LC-DASH,'Class),IndicatorFeature(individual),IndicatorFeature(investors),WordFeature(-LC-al,'Class),IndicatorFeature(money),IndicatorFeature(managers),IndicatorFeature(They),IndicatorFeature(make),IndicatorFeature(agency),IndicatorFeature(changes),IndicatorFeature(proposed),IndicatorFeature(this),IndicatorFeature(past),IndicatorFeature(that),IndicatorFeature(among),IndicatorFeature(other),IndicatorFeature(things),IndicatorFeature(many),IndicatorFeature(own),IndicatorFeature(companies),IndicatorFeature('),IndicatorFeature(shares),IndicatorFeature(also),IndicatorFeature(allow),IndicatorFeature(report),IndicatorFeature(options),IndicatorFeature(later),IndicatorFeature(less),IndicatorFeature(often),IndicatorFeature(Many),IndicatorFeature(investor),IndicatorFeature(so),IndicatorFeature(1987),IndicatorFeature(market),IndicatorFeature(--),IndicatorFeature(already),IndicatorFeature(against),IndicatorFeature(little),IndicatorFeature(any),IndicatorFeature(might),IndicatorFeature(get),IndicatorFeature(out),IndicatorFeature(stocks),IndicatorFeature(paid),IndicatorFeature(level),IndicatorFeature(one),IndicatorFeature(received),IndicatorFeature(since),IndicatorFeature(were),IndicatorFeature(17),WordFeature(-INITC-ly,'Class),WordFeature(-LC-ion,'Class),IndicatorFeature(did),IndicatorFeature(really),IndicatorFeature(believe),IndicatorFeature(rules),IndicatorFeature(force),IndicatorFeature(directors),IndicatorFeature(within),IndicatorFeature(month),IndicatorFeature(after),IndicatorFeature(transaction),IndicatorFeature(But),IndicatorFeature(25),IndicatorFeature(%),IndicatorFeature(according),IndicatorFeature(figures),IndicatorFeature(reports),IndicatorFeature(late),IndicatorFeature(effort),IndicatorFeature(federal),IndicatorFeature(boost),IndicatorFeature(who),IndicatorFeature(special),IndicatorFeature(office),IndicatorFeature(policy),IndicatorFeature(which),IndicatorFeature(officials),IndicatorFeature(had),IndicatorFeature(until),IndicatorFeature(today),IndicatorFeature(comment),IndicatorFeature(issue),IndicatorFeature(more),IndicatorFeature(than),IndicatorFeature(almost),IndicatorFeature(Mr.),IndicatorFeature(probably),IndicatorFeature(vote),IndicatorFeature(early),IndicatorFeature(next),IndicatorFeature(all),IndicatorFeature(those),IndicatorFeature(Committee),IndicatorFeature(Federal),WordFeature(-INITC-ion,'Class),IndicatorFeature(American),IndicatorFeature(Association),IndicatorFeature(example),IndicatorFeature({),IndicatorFeature(law),IndicatorFeature(}),IndicatorFeature(business),IndicatorFeature(What),IndicatorFeature(most),IndicatorFeature(is),IndicatorFeature(effect),IndicatorFeature(they),IndicatorFeature(say),IndicatorFeature(have),WordFeature(-LC-ity,'Class),IndicatorFeature(trading),IndicatorFeature(activity),IndicatorFeature(buying),IndicatorFeature(or),IndicatorFeature(selling),IndicatorFeature(director),IndicatorFeature(short),IndicatorFeature(period),IndicatorFeature(time),WordFeature(-INITC-ing,'Class),IndicatorFeature(estimates),IndicatorFeature(cut),IndicatorFeature(third),IndicatorFeature(such),IndicatorFeature(marketing),IndicatorFeature(finance),IndicatorFeature(research),IndicatorFeature(development),IndicatorFeature(still),IndicatorFeature(required),IndicatorFeature(annual),IndicatorFeature(under),IndicatorFeature(least),IndicatorFeature(if),IndicatorFeature(following),IndicatorFeature(Robert),IndicatorFeature(North),IndicatorFeature(data),IndicatorFeature(key),IndicatorFeature(may),IndicatorFeature(while),IndicatorFeature(them),IndicatorFeature(when),IndicatorFeature(do),IndicatorFeature(want),IndicatorFeature(change),IndicatorFeature(should),IndicatorFeature(Congress),IndicatorFeature(added),IndicatorFeature(likely),IndicatorFeature(legislation),IndicatorFeature(basis),IndicatorFeature(nation),IndicatorFeature(largest),IndicatorFeature(fund),IndicatorFeature($),IndicatorFeature(billion),IndicatorFeature(employees),IndicatorFeature(plans),IndicatorFeature(offer),IndicatorFeature(two),IndicatorFeature(investment),IndicatorFeature(million),WordFeature(-INITC-ity,'Class),IndicatorFeature(bond),WordFeature(-LC-est,'Class),IndicatorFeature(Both),IndicatorFeature(funds),IndicatorFeature(expected),IndicatorFeature(begin),IndicatorFeature(around),IndicatorFeature(March),IndicatorFeature(1),IndicatorFeature(subject),IndicatorFeature(approval),IndicatorFeature(For),IndicatorFeature(up),IndicatorFeature(must),IndicatorFeature(plan),IndicatorFeature(Some),IndicatorFeature(institutions),IndicatorFeature(part),IndicatorFeature(agreement),IndicatorFeature(pressure),IndicatorFeature(provide),IndicatorFeature(reached),IndicatorFeature(with),IndicatorFeature(December),IndicatorFeature(securities),IndicatorFeature(South),IndicatorFeature(power),IndicatorFeature(cases),IndicatorFeature(investments),IndicatorFeature(significant),IndicatorFeature(going),IndicatorFeature(into),IndicatorFeature(bonds),IndicatorFeature(including),IndicatorFeature(much),IndicatorFeature(foreign),IndicatorFeature(buy),IndicatorFeature(sell),IndicatorFeature(futures),IndicatorFeature(contracts),IndicatorFeature(New),IndicatorFeature(York),IndicatorFeature(State),IndicatorFeature(Department),IndicatorFeature(Under),IndicatorFeature(able),IndicatorFeature(receive),IndicatorFeature(cash),IndicatorFeature(offered),IndicatorFeature(currently),IndicatorFeature(limited),IndicatorFeature(Co.),IndicatorFeature(equipment),IndicatorFeature(shareholders),IndicatorFeature(right),IndicatorFeature(purchase),IndicatorFeature(half),IndicatorFeature(price),IndicatorFeature(certain),IndicatorFeature(takeover),IndicatorFeature(years),IndicatorFeature(old),IndicatorFeature(senior),IndicatorFeature(vice),IndicatorFeature(concern),IndicatorFeature(technology),IndicatorFeature(group),IndicatorFeature(position),IndicatorFeature(work),IndicatorFeature(lot),IndicatorFeature(because),IndicatorFeature(taken),IndicatorFeature(hard),IndicatorFeature(line),IndicatorFeature(problem),IndicatorFeature(:),IndicatorFeature(He),IndicatorFeature(does),IndicatorFeature(same),IndicatorFeature(over),IndicatorFeature(again),IndicatorFeature(Richard),IndicatorFeature(ago),IndicatorFeature(very),IndicatorFeature(like),IndicatorFeature(dropped),IndicatorFeature(though),IndicatorFeature(now),IndicatorFeature(show),IndicatorFeature(few),IndicatorFeature(thing),WordFeature(-INITC-DASH,'Class),IndicatorFeature(you),IndicatorFeature(ca),IndicatorFeature(his),IndicatorFeature(commercial),IndicatorFeature(what),IndicatorFeature(His),IndicatorFeature(recent),WordFeature(-INITC-al,'Class),IndicatorFeature(case),IndicatorFeature(point),IndicatorFeature(It),IndicatorFeature(black),IndicatorFeature(suit),IndicatorFeature(announced),IndicatorFeature(just),IndicatorFeature(family),IndicatorFeature(her),WordFeature(-CAPS-DASH-s,'Class),IndicatorFeature(no),IndicatorFeature(could),IndicatorFeature(well),IndicatorFeature(second),IndicatorFeature(And),IndicatorFeature(went),IndicatorFeature(through),IndicatorFeature(first),IndicatorFeature(longer),IndicatorFeature(five),IndicatorFeature(An),IndicatorFeature(beginning),IndicatorFeature(lead),IndicatorFeature(high),IndicatorFeature(off),IndicatorFeature(Air),IndicatorFeature(him),IndicatorFeature(great),IndicatorFeature(then),IndicatorFeature(way),IndicatorFeature(end),IndicatorFeature(however),IndicatorFeature(ever),IndicatorFeature(but),IndicatorFeature(too),IndicatorFeature(away),IndicatorFeature(That),IndicatorFeature(before),IndicatorFeature(during),IndicatorFeature(?),IndicatorFeature(take),IndicatorFeature(us),IndicatorFeature(11),IndicatorFeature(1\/2),IndicatorFeature(without),IndicatorFeature(having),IndicatorFeature(future),IndicatorFeature(can),IndicatorFeature(only),IndicatorFeature(performance),IndicatorFeature(One),IndicatorFeature(President),IndicatorFeature(international),IndicatorFeature(fact),IndicatorFeature(world),IndicatorFeature(This),IndicatorFeature(members),IndicatorFeature(United),IndicatorFeature(Now),IndicatorFeature(Bush),IndicatorFeature(decision),IndicatorFeature(we),IndicatorFeature(think),IndicatorFeature(along),IndicatorFeature(left),IndicatorFeature(financial),IndicatorFeature(top),IndicatorFeature(got),IndicatorFeature(personal),IndicatorFeature(several),IndicatorFeature(plants),IndicatorFeature(France),IndicatorFeature(sent),IndicatorFeature(even),IndicatorFeature(projects),IndicatorFeature(continue),IndicatorFeature(International),IndicatorFeature(means),IndicatorFeature(West),IndicatorFeature(pay),IndicatorFeature(World),IndicatorFeature(give),IndicatorFeature(government),IndicatorFeature(rights),IndicatorFeature(;),IndicatorFeature(held),IndicatorFeature(support),IndicatorFeature(impact),IndicatorFeature(Soviet),IndicatorFeature(holding),IndicatorFeature(seems),IndicatorFeature(current),IndicatorFeature(public),IndicatorFeature(charge),IndicatorFeature(programs),IndicatorFeature(former),IndicatorFeature(head),IndicatorFeature(military),WordFeature(-LC-DASH-s,'Class),IndicatorFeature(division),IndicatorFeature(staff),IndicatorFeature(working),IndicatorFeature(once),IndicatorFeature(budget),IndicatorFeature(changed),IndicatorFeature(John),IndicatorFeature(state),IndicatorFeature(told),IndicatorFeature(soon),IndicatorFeature(week),IndicatorFeature(raise),WordFeature(-LC-NUM-DASH,'Class),IndicatorFeature(French),IndicatorFeature(owns),IndicatorFeature(Other),IndicatorFeature(countries),IndicatorFeature(Germany),IndicatorFeature(continued),IndicatorFeature(We),IndicatorFeature(see),IndicatorFeature(free),IndicatorFeature(course),IndicatorFeature(made),IndicatorFeature(largely),IndicatorFeature(these),IndicatorFeature(home),IndicatorFeature(times),IndicatorFeature(there),IndicatorFeature(reason),IndicatorFeature(Western),IndicatorFeature(Systems),IndicatorFeature(number),IndicatorFeature(plant),IndicatorFeature(production),IndicatorFeature(itself),IndicatorFeature(another),IndicatorFeature(known),IndicatorFeature(similar),IndicatorFeature(seen),IndicatorFeature(especially),IndicatorFeature(subsidiary),IndicatorFeature(producers),IndicatorFeature(On),IndicatorFeature(process),IndicatorFeature(each),IndicatorFeature(making),IndicatorFeature(using),WordFeature(-LC-NUM-s,'Class),IndicatorFeature(20),IndicatorFeature(majority),IndicatorFeature(difficult),IndicatorFeature(China),IndicatorFeature(workers),IndicatorFeature(country),IndicatorFeature(At),IndicatorFeature(major),IndicatorFeature(Canada),IndicatorFeature(University),IndicatorFeature(California),IndicatorFeature(every),IndicatorFeature(hurt),IndicatorFeature(order),IndicatorFeature(large),IndicatorFeature(enough),IndicatorFeature(produce),IndicatorFeature(yield),IndicatorFeature(30),IndicatorFeature(used),IndicatorFeature(include),IndicatorFeature(need),IndicatorFeature(costs),IndicatorFeature(demand),IndicatorFeature(Co),IndicatorFeature(problems),IndicatorFeature(However),IndicatorFeature(Paul),IndicatorFeature(Corp.),IndicatorFeature(Calif.),IndicatorFeature(called),IndicatorFeature(remains),IndicatorFeature(active),IndicatorFeature(days),IndicatorFeature(rather),IndicatorFeature(There),IndicatorFeature(acquire),IndicatorFeature(try),IndicatorFeature(between),IndicatorFeature(Bank),IndicatorFeature(Japan),IndicatorFeature('re),IndicatorFeature(being),IndicatorFeature(latest),IndicatorFeature(50),IndicatorFeature(Japanese),IndicatorFeature(banks),IndicatorFeature(led),IndicatorFeature(help),IndicatorFeature(loans),IndicatorFeature(bank),IndicatorFeature(owned),IndicatorFeature(put),IndicatorFeature(financing),IndicatorFeature(biggest),IndicatorFeature(far),IndicatorFeature(domestic),IndicatorFeature(issues),IndicatorFeature(3),IndicatorFeature(dollars),IndicatorFeature(4),IndicatorFeature(come),IndicatorFeature(fiscal),IndicatorFeature(June),IndicatorFeature(With),IndicatorFeature(here),IndicatorFeature(David),IndicatorFeature(Tuesday),IndicatorFeature(Ltd.),IndicatorFeature(National),IndicatorFeature(I),IndicatorFeature(interests),IndicatorFeature(banking),IndicatorFeature(lower),IndicatorFeature(months),IndicatorFeature(Meanwhile),IndicatorFeature(smaller),IndicatorFeature(seeking),IndicatorFeature(open),IndicatorFeature(full),IndicatorFeature(competition),IndicatorFeature(capital),IndicatorFeature(run),IndicatorFeature(both),IndicatorFeature(businesses),IndicatorFeature(started),IndicatorFeature(venture),IndicatorFeature(use),IndicatorFeature(accounts),IndicatorFeature(account),IndicatorFeature(London),IndicatorFeature(move),IndicatorFeature(brokerage),IndicatorFeature(firms),IndicatorFeature(simply),IndicatorFeature(reported),IndicatorFeature(third-quarter),IndicatorFeature(earnings),IndicatorFeature(yesterday),IndicatorFeature(average),IndicatorFeature(analysts),IndicatorFeature(higher),IndicatorFeature(named),IndicatorFeature(industrial),IndicatorFeature(systems),IndicatorFeature(A.),IndicatorFeature(Monday),IndicatorFeature(equity),IndicatorFeature(As),IndicatorFeature(manager),IndicatorFeature(different),IndicatorFeature(four),IndicatorFeature(Series),IndicatorFeature(says),IndicatorFeature(long),IndicatorFeature(good),IndicatorFeature(television),IndicatorFeature(contract),IndicatorFeature(near),IndicatorFeature(down),IndicatorFeature(involved),IndicatorFeature(always),IndicatorFeature(You),IndicatorFeature(hit),IndicatorFeature(lawyers),IndicatorFeature(real),IndicatorFeature(estate),IndicatorFeature(better),IndicatorFeature(never),IndicatorFeature(car),IndicatorFeature(six),IndicatorFeature(James),IndicatorFeature(When),IndicatorFeature(offering),IndicatorFeature(available),IndicatorFeature(life),IndicatorFeature(back),IndicatorFeature(clear),IndicatorFeature(themselves),IndicatorFeature(something),IndicatorFeature(close),IndicatorFeature(Washington),IndicatorFeature(claims),IndicatorFeature(insurance),IndicatorFeature(Texas),IndicatorFeature(team),IndicatorFeature(me),IndicatorFeature(White),WordFeature(-CAPS-y,'Class),IndicatorFeature(Big),IndicatorFeature(These),IndicatorFeature(While),IndicatorFeature(getting),IndicatorFeature(man),IndicatorFeature(magazine),IndicatorFeature(people),IndicatorFeature(Most),IndicatorFeature(others),IndicatorFeature(recently),IndicatorFeature('m),IndicatorFeature(look),IndicatorFeature(whether),IndicatorFeature(So),IndicatorFeature(base),IndicatorFeature(Still),IndicatorFeature(how),IndicatorFeature(expect),IndicatorFeature(three),IndicatorFeature(Even),IndicatorFeature(If),IndicatorFeature(know),IndicatorFeature(wo),IndicatorFeature(lost),IndicatorFeature(become),IndicatorFeature(control),IndicatorFeature(keep),IndicatorFeature(After),IndicatorFeature(disclosed),IndicatorFeature(operations),IndicatorFeature(local),IndicatorFeature(service),IndicatorFeature(states),IndicatorFeature(build),IndicatorFeature(gas),IndicatorFeature(acquisition),IndicatorFeature(April),IndicatorFeature(completed),IndicatorFeature(common),IndicatorFeature(outstanding),IndicatorFeature(assets),IndicatorFeature(department),IndicatorFeature(Nov.),IndicatorFeature(previously),IndicatorFeature(operating),IndicatorFeature(retail),IndicatorFeature(Bay),IndicatorFeature(October),IndicatorFeature(31),IndicatorFeature(1989),IndicatorFeature(interest),IndicatorFeature(rates),IndicatorFeature(below),IndicatorFeature(general),IndicatorFeature(levels),WordFeature(-CAPS-al,'Class),IndicatorFeature(9),IndicatorFeature(8),IndicatorFeature(low),IndicatorFeature(7\/8),IndicatorFeature(bid),IndicatorFeature(traded),IndicatorFeature(Inc),IndicatorFeature(7),IndicatorFeature(3\/4),IndicatorFeature(brokers),IndicatorFeature(exchange),WordFeature(-CAPS-er,'Class),IndicatorFeature(General),IndicatorFeature(60),IndicatorFeature(150),IndicatorFeature(notes),IndicatorFeature(dealers),IndicatorFeature(Average),IndicatorFeature(unit),IndicatorFeature(credit),IndicatorFeature(5\/8),IndicatorFeature(3\/8),WordFeature(-CAPS-ed,'Class),IndicatorFeature(dollar),IndicatorFeature(auction),IndicatorFeature(bills),IndicatorFeature(face),IndicatorFeature(value),IndicatorFeature(units),IndicatorFeature(13),IndicatorFeature(weeks),IndicatorFeature(mortgage),IndicatorFeature(2),WordFeature(-CAPS-ion,'Class),IndicatorFeature(priced),IndicatorFeature(return),IndicatorFeature(returns),IndicatorFeature(product),IndicatorFeature(rose),IndicatorFeature(August),IndicatorFeature(result),IndicatorFeature(year-earlier),IndicatorFeature(total),IndicatorFeature(goods),IndicatorFeature(services),IndicatorFeature(July),IndicatorFeature(index),IndicatorFeature(September),IndicatorFeature(decline),IndicatorFeature(industry),IndicatorFeature(Dow),IndicatorFeature(Jones),IndicatorFeature(acquired),IndicatorFeature(Financial),IndicatorFeature(loan),IndicatorFeature(losses),IndicatorFeature(construction),IndicatorFeature(caused),IndicatorFeature(previous),IndicatorFeature(sale),IndicatorFeature(asked),IndicatorFeature(British),IndicatorFeature(Jaguar),IndicatorFeature(PLC),IndicatorFeature(House),IndicatorFeature(best),IndicatorFeature(quickly),IndicatorFeature(possible),IndicatorFeature(leading),IndicatorFeature(Ford),IndicatorFeature(trying),IndicatorFeature(GM),IndicatorFeature(joint),IndicatorFeature(stake),IndicatorFeature(action),IndicatorFeature(management),IndicatorFeature(deal),IndicatorFeature(European),IndicatorFeature(analyst),IndicatorFeature(Stock),IndicatorFeature(gain),IndicatorFeature(heavy),IndicatorFeature(volume),IndicatorFeature(closed),IndicatorFeature(Analysts),IndicatorFeature(#),IndicatorFeature(Sept.),IndicatorFeature(independent),IndicatorFeature(wants),IndicatorFeature(huge),IndicatorFeature(Institute),IndicatorFeature(talks),IndicatorFeature(agreed),IndicatorFeature(either),IndicatorFeature(start),IndicatorFeature(statement),IndicatorFeature(board),IndicatorFeature(holders),IndicatorFeature(meeting),IndicatorFeature(noted),IndicatorFeature(call),IndicatorFeature(declined),IndicatorFeature(our),IndicatorFeature(further),IndicatorFeature(Although),IndicatorFeature(yet),IndicatorFeature(long-term),IndicatorFeature(taking),IndicatorFeature(risk),IndicatorFeature(administration),IndicatorFeature(done),IndicatorFeature(economy),IndicatorFeature(Mrs.),IndicatorFeature(America),IndicatorFeature(revenue),IndicatorFeature(William),IndicatorFeature(additional),IndicatorFeature(chairman),IndicatorFeature(parent),IndicatorFeature(due),IndicatorFeature(parts),IndicatorFeature(D.),IndicatorFeature(J.),IndicatorFeature(nine),IndicatorFeature(ended),IndicatorFeature(net),IndicatorFeature(loss),IndicatorFeature(compared),IndicatorFeature(national),IndicatorFeature(Sales),IndicatorFeature(fell),IndicatorFeature(earlier),IndicatorFeature(ahead),IndicatorFeature(12),IndicatorFeature(showed),IndicatorFeature(Tokyo),IndicatorFeature(points),IndicatorFeature(First),IndicatorFeature(estimated),IndicatorFeature(failed),IndicatorFeature(bought),IndicatorFeature(official),IndicatorFeature(profits),IndicatorFeature(despite),IndicatorFeature(political),IndicatorFeature(14),IndicatorFeature(inflation),IndicatorFeature(consumer),IndicatorFeature(prices),IndicatorFeature(economic),IndicatorFeature(oil),IndicatorFeature(although),IndicatorFeature(supply),IndicatorFeature(day),IndicatorFeature(gains),IndicatorFeature(traders),IndicatorFeature(40),IndicatorFeature(gained),IndicatorFeature(turned),IndicatorFeature(news),IndicatorFeature(Friday),IndicatorFeature(yen),IndicatorFeature(Wall),IndicatorFeature(Street),IndicatorFeature(makers),IndicatorFeature(scheduled),IndicatorFeature(currency),IndicatorFeature(helped),IndicatorFeature(health),IndicatorFeature(Hong),IndicatorFeature(Kong),IndicatorFeature(Morgan),IndicatorFeature(Capital),IndicatorFeature(To),IndicatorFeature(100),IndicatorFeature(percentage),IndicatorFeature(food),IndicatorFeature(rise),IndicatorFeature(above),IndicatorFeature(strong),IndicatorFeature(orders),IndicatorFeature(measure),IndicatorFeature(name),IndicatorFeature(5),IndicatorFeature(Board),IndicatorFeature(increase),IndicatorFeature(terms),IndicatorFeature(slightly),IndicatorFeature(Treasury),IndicatorFeature(bill),IndicatorFeature(considered),IndicatorFeature(increases),IndicatorFeature(Among),IndicatorFeature(range),IndicatorFeature(San),IndicatorFeature(Francisco),IndicatorFeature(my),IndicatorFeature(go),IndicatorFeature(kind),IndicatorFeature(500),IndicatorFeature(6),IndicatorFeature(began),IndicatorFeature(came),IndicatorFeature(hold),IndicatorFeature(turn),IndicatorFeature(view),IndicatorFeature(your),IndicatorFeature(coming),IndicatorFeature(doing),IndicatorFeature(whose),WordFeature(-LC-NUM-DASH-s,'Class),IndicatorFeature(where),IndicatorFeature(aid),IndicatorFeature(included),IndicatorFeature(efforts),IndicatorFeature(fall),IndicatorFeature(saying),IndicatorFeature(damage),IndicatorFeature(drop),IndicatorFeature(reduce),IndicatorFeature(Fed),IndicatorFeature(Chairman),IndicatorFeature(Rep.),IndicatorFeature(instead),IndicatorFeature(spokesman),IndicatorFeature(German),IndicatorFeature(trade),IndicatorFeature(firm),IndicatorFeature(Michael),IndicatorFeature(partner),IndicatorFeature(defense),IndicatorFeature(raised),IndicatorFeature(potential),IndicatorFeature(leader),IndicatorFeature(seem),IndicatorFeature(Airlines),IndicatorFeature(1988),IndicatorFeature(nearly),IndicatorFeature(Pacific),IndicatorFeature(area),IndicatorFeature(gold),IndicatorFeature(growing),IndicatorFeature(income),IndicatorFeature(By),IndicatorFeature(results),IndicatorFeature(given),IndicatorFeature(Dec.),IndicatorFeature(quarter),IndicatorFeature(approved),IndicatorFeature(18),IndicatorFeature(airline),IndicatorFeature(network),IndicatorFeature(Drexel),IndicatorFeature(leaders),IndicatorFeature(Senate),IndicatorFeature(program),IndicatorFeature(includes),IndicatorFeature(history),IndicatorFeature(labor),IndicatorFeature(small),IndicatorFeature(meet),IndicatorFeature(job),IndicatorFeature(toward),IndicatorFeature(tax),IndicatorFeature(thought),IndicatorFeature(Industries),WordFeature(-INITC-NUM-DASH,'Class),IndicatorFeature(debt),IndicatorFeature(paper),IndicatorFeature(situation),IndicatorFeature(manufacturing),IndicatorFeature(profit),IndicatorFeature(planned),IndicatorFeature(composite),IndicatorFeature(fourth),IndicatorFeature(particularly),IndicatorFeature(reduced),IndicatorFeature(found),IndicatorFeature(All),IndicatorFeature(Boston),IndicatorFeature(settlement),IndicatorFeature(charges),IndicatorFeature(customers),IndicatorFeature(computers),IndicatorFeature(East),IndicatorFeature(system),IndicatorFeature(1986),IndicatorFeature(lines),IndicatorFeature(legal),IndicatorFeature(took),IndicatorFeature(Corp),WordFeature(-CAPS-NUM,'Class),IndicatorFeature(cost),IndicatorFeature(concerns),IndicatorFeature(she),IndicatorFeature(Last),IndicatorFeature(Group),IndicatorFeature(amount),IndicatorFeature(deficit),IndicatorFeature(issued),IndicatorFeature(Trust),IndicatorFeature(spending),IndicatorFeature(bad),IndicatorFeature(big),IndicatorFeature(question),IndicatorFeature(city),IndicatorFeature('ve),IndicatorFeature(house),IndicatorFeature('ll),IndicatorFeature(attorney),IndicatorFeature(dividend),IndicatorFeature(16),WordFeature(-CAPS-est,'Class),IndicatorFeature(payments),IndicatorFeature(trust),IndicatorFeature(portfolio),IndicatorFeature(note),IndicatorFeature(addition),IndicatorFeature(Judge),IndicatorFeature(judge),IndicatorFeature(steel),IndicatorFeature(court),IndicatorFeature(find),IndicatorFeature(areas),IndicatorFeature(clients),IndicatorFeature(outside),IndicatorFeature(Court),IndicatorFeature(...),IndicatorFeature(hours),IndicatorFeature(filing),IndicatorFeature(filed),IndicatorFeature(Union),IndicatorFeature(earthquake),IndicatorFeature(private),IndicatorFeature(1\/4),IndicatorFeature(S&P),IndicatorFeature(Merrill),IndicatorFeature(Lynch),WordFeature(-INITC-est,'Class),IndicatorFeature(via),IndicatorFeature(200),IndicatorFeature(marks),IndicatorFeature(Revenue),IndicatorFeature(taxes),IndicatorFeature(creditors),IndicatorFeature(Since),IndicatorFeature(strategy),IndicatorFeature(Canadian),IndicatorFeature(property),IndicatorFeature(IBM),IndicatorFeature(Business),IndicatorFeature(place),IndicatorFeature(needed),IndicatorFeature(jumped),IndicatorFeature(project),IndicatorFeature(Warner),IndicatorFeature(CBS),IndicatorFeature(committee),IndicatorFeature(advertising),IndicatorFeature(ad),IndicatorFeature(`),IndicatorFeature(campaign),IndicatorFeature(stores),WordFeature(-CAPS-ing,'Class),WordFeature(-CAPS-NUM-DASH,'Class),IndicatorFeature(pilots),IndicatorFeature(estimate),IndicatorFeature(calls),IndicatorFeature(union),IndicatorFeature(drug),IndicatorFeature(important),IndicatorFeature(adds),IndicatorFeature(eight),WordFeature(-INITC-NUM,'Class),IndicatorFeature(George),IndicatorFeature(groups),IndicatorFeature(conference),IndicatorFeature(looking),IndicatorFeature(TV),IndicatorFeature(quake),IndicatorFeature(posted),IndicatorFeature(related),IndicatorFeature(Sen.),IndicatorFeature(22),IndicatorFeature(Wednesday),IndicatorFeature(reserves),IndicatorFeature(restructuring),IndicatorFeature(buyers),IndicatorFeature(buy-out),IndicatorFeature(Shearson),IndicatorFeature(UAL),IndicatorFeature(francs),IndicatorFeature(1\/8),WordFeature(-INITC-DASH-s,'Class),IndicatorFeature(junk),IndicatorFeature(study),IndicatorFeature(Thursday),IndicatorFeature(abortion),WordFeature(-CAPS-NUM-DASH-s,'Class),IndicatorFeature(Noriega),WordFeature(-CAPS-ly,'Class),WordFeature(-INITC-NUM-DASH-s,'Class),WordFeature(-CAPS-ity,'Class),WordFeature(-INITC-NUM-s,'Class))
[error] at epic.features.IndexedWordFeaturizer$.epic$features$IndexedWordFeaturizer$$stripEncode(IndexedWordFeaturizer.scala:56)
[error] at epic.features.IndexedWordFeaturizer$MyWordFeaturizer$$anonfun$1.apply(IndexedWordFeaturizer.scala:39)
[error] at epic.features.IndexedWordFeaturizer$MyWordFeaturizer$$anonfun$1.apply(IndexedWordFeaturizer.scala:39)
[error] at scala.Array$.tabulate(Array.scala:331)
[error] at epic.features.IndexedWordFeaturizer$MyWordFeaturizer.anchor(IndexedWordFeaturizer.scala:39)
[error] at epic.sequences.TaggedSequenceModelFactory$IndexedStandardFeaturizer$$anon$2.<init>(CRFModel.scala:207)
[error] at epic.sequences.TaggedSequenceModelFactory$IndexedStandardFeaturizer.anchor(CRFModel.scala:205)
[error] at epic.sequences.CRFInference$Anchoring.<init>(CRFModel.scala:99)
[error] at epic.sequences.CRFInference.anchor(CRFModel.scala:79)
[error] at epic.sequences.CRFInference.anchor(CRFModel.scala:58)
[error] at epic.sequences.CRF$class.bestSequence(CRF.scala:42)
[error] at epic.sequences.CRFInference.bestSequence(CRFModel.scala:58)
[error] at scraper$$anonfun$9.apply(main.scala:81)
[error] at scraper$$anonfun$9.apply(main.scala:57)
[error] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
[error] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
[error] at scala.collection.Iterator$class.foreach(Iterator.scala:891)
[error] at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
[error] at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
[error] at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
[error] at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
[error] at scala.collection.AbstractTraversable.map(Traversable.scala:104)
[error] at scraper$.delayedEndpoint$scraper$1(main.scala:57)
[error] at scraper$delayedInit$body.apply(main.scala:17)
[error] at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
[error] at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
[error] at scala.App$$anonfun$main$1.apply(App.scala:76)
[error] at scala.App$$anonfun$main$1.apply(App.scala:76)
[error] at scala.collection.immutable.List.foreach(List.scala:392)
[error] at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
[error] at scala.App$class.main(App.scala:76)
[error] at scraper$.main(main.scala:17)
[error] at scraper.main(main.scala)
[error] at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
[error] at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
[error] at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
[error] at java.lang.reflect.Method.invoke(Method.java:498)
[error] Nonzero exit code: 1
[error] (Compile / run) Nonzero exit code: 1
Hi there,
I'm trying to use epic in an Apache Spark Streaming environment but I'm experiencing some difficulty loading the models. I'm not really sure whether this is an Epic issue, a Breeze issue, a Spark issue or where/how to solve this now! I get the following exception (for English NER):
Exception in thread "main" java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.HashMap$SerializationProxy to field epic.features.BrownClusterFeaturizer.epic$features$BrownClusterFeaturizer$$clusterFeatures of type scala.collection.immutable.Map in instance of epic.features.BrownClusterFeaturizer
at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2083)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1261)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1996)
... trimmed ...
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
at breeze.util.package$.readObject(package.scala:21)
at epic.models.package$.deserialize(package.scala:54)
... trimmed calls from my code ...
I've tried running my code (compiled into uberjar using 'sbt assembly') in a raw scala console and I can load the model and run it fine. However, using Spark, I get the exception described. The ONLY difference as far as I can tell is the way the model file is referenced. For the raw scala environment, I can point directly at the model file on disk (e.g. new File("mymodels/model.ser.gz")) and it loads. In Spark, I have to load the file doing something similar to:
sc.addFile("model.ser.gz")
new File(SparkFiles.get("model.ser.gz")
I've tried narrowing the code down and depending whether I point at the model extracted from the jar or the jar itself I get the same result. It's definitely loading the file (I think) as it fails in other ways if the file doesn't exist. I even tried bypassing the Breeze nonStupidObjectInputStream to no avail.
Any idea what's going on or how to test? For reference, my JVM is 1.7.0_51 and same in both scala and Spark environments.
Thanks.
Got the model (from here: http://www.scalanlp.org/models/ ) and put it into the project home
Then:
val tagger = epic.models.deserialize[CRF[AnnotatedLabel, String]]("model.ser.gz") {code}
But still have exception:
Exception in thread "main" java.lang.RuntimeException: Could not find model model.ser.gz in path /home/myuser/projects/nlp/epic-mast
But the model file is definitely there
Via typeclasses or implicit String enhancement.
Hi Epic Team,
I love using your library but get an error when using the english parser in scala 2.10:
Exception in thread "main" java.io.InvalidClassException: breeze.linalg.Counter2$$anon$1; local class incompatible: stream classdesc serialVersionUID = -8653601685403516672, local class serialVersionUID = 6118148492784004600
at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:621)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1623)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readArray(ObjectInputStream.java:1707)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1345)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at epic.models.ClassPathModelLoader.load(ModelLoader.scala:23)
at epic.models.DelegatingLoader.load(ModelLoader.scala:33)
at epic.models.PosTagSelector$.loadTagger(PosTagModelLoader.scala:13)
at de.unima.dws.oamatching.measures.StringMeasureHelper$.addPosTag(StringMeasureHelper.scala:116)
at de.unima.dws.oamatching.measures.StringMeasureHelper$delayedInit$body.apply(StringMeasureHelper.scala:18)
at scala.Function0$class.apply$mcV$sp(Function0.scala:40)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:71)
at scala.App$$anonfun$main$1.apply(App.scala:71)
at scala.collection.immutable.List.foreach(List.scala:318)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:32)
at scala.App$class.main(App.scala:71)
at de.unima.dws.oamatching.measures.StringMeasureHelper$.main(StringMeasureHelper.scala:15)
at de.unima.dws.oamatching.measures.StringMeasureHelper.main(StringMeasureHelper.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:134)
Fails with
[info] - chain rule 2 *** FAILED ***
[info] 0.004569766477666382 was bigger than expected!! (AffineTransformTest.scala:51)
java -Xmx1g -cp target/scala-2.10/epic-assembly-0.2-SNAPSHOT.jar epic.parser.models.ParserTrainer --treebank.path wsj --modelFactory epic.parser.models.SpanModelFactory --maxLength 10
whichmaven dependency of the models (POS & NER ) should I have to pick with 0.4-SNAPSHOT release?
I tried:
"org.scalanlp" %% "english" % "2015.1.25"
and other older releases, but when I do
val ner = epic.models.NerSelector.loadNer("en").get
I keep on getting serialization errors.
Hi @dlwh,
first off, thanks for making Epic available, it's a great tool!
I have a "parsing" problem where I would like to restrict the search space to a fully segmented binarized tree and would like to use the neural parser to only do the labelling for me (the trees come from a customized treebank that I pass to epic for training). I have been trying to do this via constraints (using GoldConstraintsFactory) in NeuralParserTrainer but so far without success. Is there any established/recommended way for using "gold spans" and only letting Epic do the labelling?
Jo
Hello. I found something...
pos-en model can't be loaded.
Tryed following code,
val tagger: CRF[AnnotatedLabel,String] = epic.models.PosTagSelector.loadTagger("en").get
and got following error,
Exception in thread "main" java.lang.NullPointerException
at java.util.zip.InflaterInputStream.<init>(InflaterInputStream.java:83)
at java.util.zip.GZIPInputStream.<init>(GZIPInputStream.java:76)
at java.util.zip.GZIPInputStream.<init>(GZIPInputStream.java:90)
at epic.models.ClassPathModelLoader.load(ModelLoader.scala:21)
at epic.models.DelegatingLoader.load(ModelLoader.scala:33)
at epic.models.PosTagSelector$.loadTagger(PosTagModelLoader.scala:13)My epic/epic-models versions:
libraryDependencies ++= Seq(
"org.scalanlp" % "epic_2.10" % "0.2-SNAPSHOT",
"org.scalanlp" %% "epic-pos-en" % "2014.6.2-SNAPSHOT",
"org.scalanlp" %% "epic-parser-en-span" % "2014.6.2-SNAPSHOT",
"org.scalanlp" %% "epic-ner-en-conll" % "2014.6.2-SNAPSHOT"
// "org.scalanlp" %% "epic-pos-en" % "0.1",
// "org.scalanlp" %% "epic-parser-en-span" % "0.1",
// "org.scalanlp" %% "epic-ner-en-conll" % "0.1"
)Hello,
How to use trained models using neural CRF parsing is not described ?
Can there be some more ways of gaining knowledge please?
At least documented code?
More examples?
The introduction clip on YouTube (https://www.youtube.com/watch?v=rpfVtRqQ4_o) explains that you can create your own features, but not how to use them. For this project to gain traction there needs to be more information. I would help writing guides etc, but I just can't get on with it, there's nothing to reference to.
/Marcus
Trained parser of polish language from http://www.scalanlp.org/models/ does not work with current master branch. I tried to run:
java -Xmx6g -cp target/scala-2.11/epic-assembly-0.4-SNAPSHOT.jar epic.parser.ParseText --model epic-parser-pl-span_2.10-2014.6.3-SNAPSHOT.jar --nthreads 4 exampleArticle.txt
and I get:
Couldn't deserialize model due to exception, epic.parser.models.ParserTrainer$$anonfun$2; local class incompatible: stream classdesc serialVersionUID = 0, local class serialVersionUID = 5531977503861241212. Trying classPathLoad...
Exception in thread "main" java.util.NoSuchElementException: None.get
at scala.None$.get(Option.scala:347)
at scala.None$.get(Option.scala:345)
at epic.parser.ParseText$.classPathLoad(ParseText.scala:21)
at epic.parser.ParseText$.classPathLoad(ParseText.scala:11)
at epic.util.ProcessTextMain$class.main(ProcessTextMain.scala:47)
at epic.parser.ParseText$.main(ParseText.scala:11)
at epic.parser.ParseText.main(ParseText.scala)
which says, that versions of classes are not the same.
I also downloaded JAR from maven repository and there is the same error.
I found at Maven that the latest version of epic is 0.4.5, but on github is 0.3. Did epic host the new version of code somewhere else, or Maven epic is a different one?
The maven repo link: https://mvnrepository.com/artifact/org.scalanlp/epic
Hi, David,
May I ask whether you have a latest release for "epic-parser-en-span" after "2014.9.15"? If not, would you please make one for both Scala 2.10 and 2.11?
Thanks!
With epic-2.11 and breeze-2.11, I get
missing or invalid dependency detected while loading class file 'SafeLogging.class'. Could not access term scalalogging in value com.typesafe, because it (or its dependencies) are missing. Check your build definition for missing or conflicting dependencies. (Re-run with -Ylog-classpath to see the problematic classpath.) A full rebuild may help if 'SafeLogging.class' was compiled against an incompatible version of com.typesafe. Epic Unknown Scala Problem
although SafeLogging is shown in the class browser in my Eclipse window.
Hi!
I try to setup the project in a Intellij 14 IDE with a Scala plugin and sbt 0.13.7
I can see a lot of errors posted by IntelliJ in build.sbt as well as in classes. However, the project compiles well, I can run sbt assembly and get a jar.
Please, write in Wiki your development environment IDE+additional tools and versions to be able to load the project without errors.
It is really hard to evaluate this library when no documentation related to usage is available.
Sorry to bother you.
In epic/target/scala-2.11
java -Xmx4g -cp epic-assembly-0.4.4.jar epic.sequences.TagText --model epic-pos-en_2.10-2014.6.3-SNAPSHOT.jar --nthreads 4 test
[main] ERROR breeze.util.HashIndex$ - Deserializing an old-style HashIndex. Taking counter measures Couldn't deserialize model due to exception, epic.features.WordFeature; local class incompatible: stream classdesc serialVersionUID = 1068855398746279726, local class serialVersionUID = 1. Trying classPathLoad... Exception in thread "main" java.util.NoSuchElementException: None.get at scala.None$.get(Option.scala:347) at scala.None$.get(Option.scala:345) at epic.sequences.TagText$.classPathLoad(TagText.scala:20) at epic.sequences.TagText$.classPathLoad(TagText.scala:11) at epic.util.ProcessTextMain$class.main(ProcessTextMain.scala:47) at epic.sequences.TagText$.main(TagText.scala:11) at epic.sequences.TagText.main(TagText.scala)
I don't know how to solve the problem, it's English model.
scala -version Scala code runner version 2.12.4 -- Copyright 2002-2017, LAMP/EPFL and Lightbend, Inc.
Hi,
Experiencing problems using the parser trainer. My goal is to train a parser with CRAFT's treebank for the biology domain; not sure if the layout of CRAFT's treebank is supported by epic or not. Tried to start out by training a parser on "smallbank" -- no luck. Any advice?
$ java -cp target/scala-2.11/epic-assembly-0.2.jar epic.parser.models.ParserTrainer \
--treebankType simple
--treebank.path "src/main/resources/smallbank"
--modelFactory epic.parser.models.SpanModelFactory
--cache.path constraints.cache
--opt.useStochastic true
--opt.regularization 1.0
[main] INFO epic.parser.models.ParserTrainer$ - Training Parser...
Exception in thread "main" java.lang.RuntimeException:
error while indexingBinaryRule(VP[^SINV], VBN[^VP], PP[^VP]) to
BinaryRule(VP, VBN, PP)0
at epic.parser.projections.ProjectionIndexer$$anonfun$apply$5.apply(ProjectionIndexer.scala:115)
...
This probably has a simple answer, but Loading the english training data through maven and calling it with NerSelector.loadNer breaks. However, calling it directly with epic.parser.models.en.span.EnglishSpanParser.load() works.
POM dependency
<dependency>
<groupId>org.scalanlp</groupId>
<artifactId>epic-parser-en-span_2.10</artifactId>
<version>0.1</version>
</dependency>Load the NerSelector
val tagger = epic.models.NerSelector.loadNer("en").get
epic.models.NerSelector.loadNer("en") returns none and explodes all over the .get
On line 24 in the ModelSelector: The serviceLoader.asScala returns 0 which causes the filter to return none.
Exception in thread "main" java.lang.NullPointerException
at org.mapdb.Volume$ByteBufferVol.getLong(Volume.java:300)
at org.mapdb.StoreDirect.checkHeaders(StoreDirect.java:112)
at org.mapdb.StoreDirect.(StoreDirect.java:100)
at org.mapdb.StoreWAL.(StoreWAL.java:46)
at org.mapdb.DBMaker.makeEngine(DBMaker.java:582)
at org.mapdb.DBMaker.make(DBMaker.java:556)
at epic.util.CacheBroker$ActualCache.db$lzycompute(Cache.scala:50)
at epic.util.CacheBroker$ActualCache.db(Cache.scala:49)
at epic.util.CacheBroker.db(Cache.scala:38)
at epic.util.CacheBroker$CacheMap.liftedTree1$1(Cache.scala:103)
at epic.util.CacheBroker$CacheMap.theMap(Cache.scala:100)
at epic.util.CacheBroker$CacheMap.getOrElseUpdate(Cache.scala:151)
at epic.constraints.CachedChartConstraintsFactory.constraints(CachedChartConstraintsFactory.scala:31)
at epic.parser.models.NeuralParserTrainer$$anonfun$trainParser$1.apply(NeuralParserTrainer.scala:113)
at epic.parser.models.NeuralParserTrainer$$anonfun$trainParser$1.apply(NeuralParserTrainer.scala:113)
at scala.collection.parallel.AugmentedIterableIterator$class.map2combiner(RemainsIterator.scala:115)
at scala.collection.parallel.immutable.ParVector$ParVectorIterator.map2combiner(ParVector.scala:62)
at scala.collection.parallel.ParIterableLike$Map.leaf(ParIterableLike.scala:1054)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Map.tryLeaf(ParIterableLike.scala:1051)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:159)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinTask.doJoin(ForkJoinTask.java:341)
at scala.concurrent.forkjoin.ForkJoinTask.join(ForkJoinTask.java:673)
at scala.collection.parallel.ForkJoinTasks$WrappedTask$class.sync(Tasks.scala:378)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.sync(Tasks.scala:443)
at scala.collection.parallel.ForkJoinTasks$class.executeAndWaitResult(Tasks.scala:426)
at scala.collection.parallel.ForkJoinTaskSupport.executeAndWaitResult(TaskSupport.scala:56)
at scala.collection.parallel.ExecutionContextTasks$class.executeAndWaitResult(Tasks.scala:558)
at scala.collection.parallel.ExecutionContextTaskSupport.executeAndWaitResult(TaskSupport.scala:80)
at scala.collection.parallel.ParIterableLike$ResultMapping.leaf(ParIterableLike.scala:958)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$ResultMapping.tryLeaf(ParIterableLike.scala:953)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:152)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Hi, recently I want to reimplement the CRF parser in another language like (C++/flex, python/boost and so on). I have read the paper "Less grammar, more features" which proposes more features for CRF model. I am trying to figure out how the parser is implemented using CRF model.
I am trying to read the source code to understand how this works. I wish some the author can help me to figure out how these two parts are implemented.
For the first part, since I am going to use Neural CRF, more details about data preprocessing are appreciated.
Have a nice weekend!
For the newbie who want to use it, sbt-0.13.11, sbt-assembly-0.14.5 are preferred. Before sbt-0.13.8, sbt is extremely slow. Community has resolved the problem recently by bumping up to 0.13.11.
When I call the French model of the dependency parser I get:
Loading parser from serialized file edu/stanford/nlp/models/lexparser/frenchFactored.ser.gz ... done [2,8 sec].
Exception in thread "main" java.io.InvalidClassException: epic.parser.models.ParserTrainer$$anonfun$2; local class incompatible: stream classdesc serialVersionUID = 0, local class serialVersionUID = 5531977503861241212
at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:621)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1623)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at epic.models.ClassPathModelLoader.load(ModelLoader.scala:23)
at epic.models.DelegatingLoader.load(ModelLoader.scala:33)
at epic.models.ParserSelector$.loadParser(ParserSelector.scala:15)
at prepare.data.Parser$.delayedEndpoint$prepare$data$Parser$1(Parser.scala:19)
at prepare.data.Parser$delayedInit$body.apply(Parser.scala:6)Seems to be very related to #26
Is there a way to download new models?
Kind regards,
Michaël
WARNING: Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS
[main] INFO epic.framework.ModelObjective - Inference took: 2.876s
[main] INFO epic.parser.models.NeuralParserTrainer$ - Validating...
[ForkJoinPool-1-worker-13] INFO epic.parser.ParseEval$ - Sentences parsed 100/100 (0.224s elapsed.)
[main] INFO epic.parser.models.NeuralParserTrainer$ - Overall statistics for validation: Statistics(precision=1, recall=0.9403, f1=0.9692, exact=0.92, tagAccuracy=1)
[main] INFO epic.dense.AdadeltaGradientDescentDVD - Step Size: 1.000
[main] INFO epic.framework.ModelObjective - Inference took: 2.660s
[main] INFO epic.dense.AdadeltaGradientDescentDVD - Val and Grad Norm: 782.761 (rel: 0.329) 1884.69
[main] INFO epic.dense.AdadeltaGradientDescentDVD - Step Size: 1.000
Exception in thread "main" java.lang.IllegalAccessError: DB has been closed
at org.mapdb.EngineWrapper.checkClosed(EngineWrapper.java:297)
at org.mapdb.CacheWeakSoftRef.get(CacheWeakSoftRef.java:123)
at org.mapdb.HTreeMap.get(HTreeMap.java:414)
at scala.collection.convert.Wrappers$JConcurrentMapWrapper.get(Wrappers.scala:323)
at scala.collection.mutable.MapLike$class.getOrElseUpdate(MapLike.scala:192)
at scala.collection.mutable.AbstractMap.getOrElseUpdate(Map.scala:80)
at epic.util.CacheBroker$CacheMap.getOrElseUpdate(Cache.scala:151)
at epic.constraints.CachedChartConstraintsFactory.constraints(CachedChartConstraintsFactory.scala:31)
at epic.parser.models.ParserInference$class.scorer(ParserModel.scala:51)
at epic.parser.models.PositionalNeuralModel$Inference.scorer(PositionalNeuralModel.scala:148)
at epic.parser.models.PositionalNeuralModel$Inference.scorer(PositionalNeuralModel.scala:148)
at epic.framework.Model$class.accumulateCounts(Model.scala:52)
at epic.parser.models.PositionalNeuralModel.accumulateCounts(PositionalNeuralModel.scala:30)
at epic.framework.ModelObjective$$anonfun$3.apply(ModelObjective.scala:68)
at epic.framework.ModelObjective$$anonfun$3.apply(ModelObjective.scala:65)
at scala.collection.parallel.mutable.ParArray$ParArrayIterator.foldLeft_quick(ParArray.scala:174)
at scala.collection.parallel.mutable.ParArray$ParArrayIterator.foldLeft(ParArray.scala:165)
at scala.collection.parallel.ParIterableLike$Aggregate.leaf(ParIterableLike.scala:1008)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply$mcV$sp(Tasks.scala:49)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$$anonfun$tryLeaf$1.apply(Tasks.scala:48)
at scala.collection.parallel.Task$class.tryLeaf(Tasks.scala:51)
at scala.collection.parallel.ParIterableLike$Aggregate.tryLeaf(ParIterableLike.scala:1005)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.internal(Tasks.scala:169)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.internal(Tasks.scala:443)
at scala.collection.parallel.AdaptiveWorkStealingTasks$WrappedTask$class.compute(Tasks.scala:149)
at scala.collection.parallel.AdaptiveWorkStealingForkJoinTasks$WrappedTask.compute(Tasks.scala:443)
at scala.concurrent.forkjoin.RecursiveAction.exec(RecursiveAction.java:160)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.