A list of Abstract meaning representation (AMR) resources: research papers, code, data, applications, etc. The list is not limited to Abstract meaning representation exclusively. It also includes work highly related to AMR, such as translation and information extraction.
- AMR Resources
抽象意义表示(Abstract Meaning Representation,AMR)是一种将句子的意义(时间地点谁对谁怎样地做了什么)表示为以概念为节点的单源有向无环图的语言学框架。AMR正在引起学术界越来越广泛的关注,已经涌现了许多利用AMR进行机器翻译、QA、关系提取等应用的工作。
Suppose we have the following input sentence:
The boy wants the girl to believe him.
AMR aims to make the following format:
(w / want-01
:ARG0 (b / boy)
:ARG1 (b2 / believe-01
:ARG0 (g / girl)
:ARG1 b))
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"Abstract Meaning Representation for Sembanking" - ACL 2013 Laura Banarescu, Claire Bonial, Shu Cai
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"Renewing and revising SemLink", -ACL 2013 Claire Bonial, Kevin Stowe & Martha Palmer
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"Unsupervised Induction of Cross-lingual Semantic Relations", -ACL 2013 M Lewis, M Steedman
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"Textual inference and meaning representation in human robot interaction", -ACL 2013 Emanuele Bastianelli Giuseppe Castellucci Danilo Croce Roberto Basili
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" A discriminative graph-based parser for the abstract meaning representation", -ACL 2014 Jeffrey Flanigan Sam Thomson Jaime Carbonell Chris Dyer Noah A. Smith
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"Large-scale Semantic Parsing without Question-Answer Pairs", ACL 2014 Siva Reddy, Mirella Lapata, Mark Steedman
smatch metric is developed for comparing one AMR against another. It computes an f-score over the semantic triples inside AMRs.
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"Smatch: an Evaluation Metric for Semantic Feature Structures," ACL 2013 (smatch code ,demo)
S. Cai and K. Knight
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"Transition-Based Dependency Parsing with Stack Long Short-Term Memory," ACL 2015 code
Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, Noah A. Smith
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"CAMR at SemEval-2016 Task 8: An Extended Transition-based AMR Parser," ACL 2016
Chuan Wang, Sameer Pradhan, Xiaoman Pan, Heng Ji, Nianwen Xue
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"Transition-based Parsing with Stack-Transformers," ACL 2020
Ramón Fernandez Astudillo, Miguel Ballesteros, Tahira Naseem, Austin Blodgett, Radu Florian
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"Deep biaffine attention for neural dependency parsing", ACL 2017 codecode
Timothy Dozat, Christopher D. Manning
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"AMR Parsing via Graph-Sequence Iterative Inference," ACL 2020 code
Deng Cai, Wai Lam
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"Levi Graph AMR Parser using Heterogeneous Attention", ACL 2021 code
Han He, Jinho D. Choi
AMR graph output has been shown to be a useful input for many downstream tasks. In this section, several downstream tasks that benefited from AMR output are listed.
AMR体现在知识库的构建和使用上,好的知识结构更有利于更新和应用。
- "Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations," -CLIN 2017 Rik van Noord, Johan Bos
- "Semantic Neural Machine Translation Using AMR", -ACL 2019 Linfeng Song, Daniel Gildea, Yue Zhang, Zhiguo Wang and Jinsong Su
- "Self-Attention with Structural Position Representations", - EMNLP 2019 Xing Wang, Zhaopeng Tu, Longyue Wang, Shuming Shi
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"Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task", - EMNLP 2018, Long Paper Tao Yu Rui Zhang Kai Yang Michihiro Yasunaga
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"TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation",- NAACL 2018 Tao Yu, Zifan Li, Zilin Zhang, Rui Zhang, Dragomir Radev
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"Leveraging Abstract Meaning Representation for Knowledge Base Question Answering", -ACL2021
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar
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"A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering", -AAAI 2021
Ibrahim Abdelaziz
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"Generation from Abstract Meaning Representation using Tree Transducers", -NAACL 2016 code
Jeffrey Flanigan,Chris Dyer,Noah A. Smith,Jaime Carbonell
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"Neural AMR: Sequence-to-Sequence Models for Parsing and Generation", -ACL 2017
Konstas, Ioannis
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"Toward Abstractive Summarization Using Semantic Representations", ACL 2018 Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh, Noah A. Smith
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"A Graph-to-Sequence Model for AMR-to-Text Generation", ACL 2018 Linfeng Song, Yue Zhang, Zhigo Wang, Daniel Gildea
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"Deep Graph Convolutional Encoders for tructured Data to Text Generation", -ACL 2018 code Diego Marcheggiani,Laura Perez-Beltrachini
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["Structural Neural Encoders for AMR-to-text Generation",](Marco Damonte, Shay B. Cohen) -NAACL 2019 code Marco Damonte, Shay B. Cohen
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"Modeling Graph Structure in Transformer for Better AMR-to-Text Generation", -EMNLP 2019 Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, Guodong Zhou
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"Enhancing AMR-to-Text Generation with Dual Graph Representations", -EMNLP 2019 code
Leonardo F. R. Ribeiro, Claire Gardent, Iryna Gurevych
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"GPT-too: A language-model-first approach for AMR-to-text generation", -ACL 2020
Manuel Mager, Ramon Fernandez Astudillo, Tahira Naseem, Md Arafat Sultan, Young-Suk Lee, Radu Florian, Salim Roukos
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"Investigating Pretrained Language Models for Graph-to-Text Generation" -2020 code
Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, Iryna Gurevych
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"Structural Information Preserving for Graph-to-Text Generation",", -ACL 2020
Linfeng Song, Ante Wang, Jinsong Su, Yue Zhang, Kun Xu, Yubin Ge, Dong Yu
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"Unsupervised Induction of Cross-lingual Semantic Relations", -ACL 2013 code M Lewis, M Steedman
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"A Joint Neural Model for Information Extraction with Global Features", -ACL 2020 code
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"Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction", -NAACL 2021 code
Zixuan Zhang and Heng Ji
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"Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation", -ACL 2021 code
Zixuan Zhang, Nikolaus Parulian, Heng Ji
- "Textual inference and meaning representation in human robot interaction", -ACL Emanuele Bastianelli Giuseppe Castellucci Danilo Croce Roberto Basili
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"Generating semantically precise scene graphs from textual descriptions for improved image retrieval", -ACL 2015 Sebastian Schuster, Ranjay Krishna, Angel Chang, Li Fei-Fei, and Christopher D. Manning
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"Genie: A Generator of Natural Language Semantic Parsers for Virtual Assistant Commands", -PLDI code
Giovanni Campagna, Silei Xu, Mehrad Moradshahi, Richard Socher, Monica S. Lam
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"Unified Visual-Semantic Embeddings: Bridging Vision and Language With Structured Meaning Representations", -CVPR 2019 H Wu, J Mao, Y Zhang, Y Jiang
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"Cross-media Structured Common Space for Multimedia Event Extraction", -ACL 2020
Manling Li, Alireza Zareian, Qi Zeng, Spencer Whitehead, Di Lu, Heng Ji, Shih-Fu Chang
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"Bootstrapping Multilingual AMR with Contextual Word Alignments", -ACL 2021
Janaki Sheth, Young-Suk Lee, Ramon Fernandez Astudillo
- "Question-Answer Driven Semantic Role Labeling:Using Natural Language to Annotate Natural Language", -EMNLP 2015 Luheng He Mike Lewis Luke Zettlemoyer
- "Cross-lingual Name Tagging and Linking for 282 Languages", -ACL 2017 Xiaoman Pan Boliang Zhang Jonathan May
- "The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations", -EACL 2017 Lasha Abzianidze Johannes Bjerva Kilian Evang Hessel Haagsma
- "Automatically Solving Number Word Problems by Semantic Parsing and Reasoning", -ACL 2015 Shuming Shi Yuehui Wangn Chin-Yew Lin Xiaojiang Liu1 and Yong Rui
- "Unsupervised Entity Linking with Abstract Meaning Representation", -ACL 2015 code Xiaoman Pan Taylor Cassidy Ulf Hermjakob Heng Ji Kevin Knight
- "Richer event description: Integrating event coreference with temporal, causal and bridging annotation", -ACL 2016 Tim O’Gorman and Kristin Wright-Bettner and Martha Palmer
- "A Syntactic Neural Model for General-Purpose Code Generation", -ACL 2017 Pengcheng Yin, Graham Neubig
- "TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation", -EMNLP 2018 Pengcheng Yin, Graham Neubig
"Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?", -ACL 2021
Abhilasha Ravichander, Alan W Black, Thomas Norton, Shomir Wilson, Norman Sadeh
- AMR 2.0 (LDC2017T10)
- AMR 3.0(LDC2020T02)
- CAMR 2.0 由布兰迪斯大学和南京师范大学联合标注的中文抽象意义表示语料库2.0