handling OOV entities about infersent

[aconneau]

I will push soon a model trained with fastText newest embeddings (trained on CommonCrawl). This way, you can use fastText feature for OOV words, and send the results embeddings to the InferSent encoder.

[proprietary]

I was wondering about this as well.

One option would be to use dynamically generated word embeddings. Facebook also has its fastText project which can generate any OOV embedding because it trains and does inference on n-grams, not words. I think it wouldn't be necessary to retrain on your specific corpus this way. I plan to test the performance from replacing GloVe vectors with fastText.

[aconneau]

I uploaded fastText model in 14b7ebb
I did not find the .bin for these vectors (crawl, https://fasttext.cc/docs/en/english-vectors.html) though, so not sure you will be able to encode the OOV words using the common-crawl English embeddings.

[aconneau]

Unfortunately fastText does not provide the .bin for the English common-crawl word embeddings so handling OOV this way is not yet possible.

See facebookresearch/fastText#428 (comment)

[aconneau]

@ncammarata: do you have concrete examples of entities from the dataset you use?

[ncammarata]

@aconneau hey sorry I missed this - I'm not working on a project that requires this anymore