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How to deal with out of vocabulary words? #24

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qasim9872 opened this issue Apr 25, 2019 · 0 comments
Open

How to deal with out of vocabulary words? #24

qasim9872 opened this issue Apr 25, 2019 · 0 comments

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@qasim9872
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Hi,

I recently utilized the technique that has been discussed in this project for transforming a natural language sentence into a SPARQL query. Based on this, I created an end to end question answering system as part of my final year project. The system works well for known resource names, however; for questions which contain out of vocabulary words (resource names/words not part of the training data), the system does not predict an accurate query.

In the Neural Machine Translation for Query Construction paper, it says that External pre-trained word embeddings help deal with vocabulary mismatch. I am not sure how this would be implemented, could you provide any insight? I am already finished with the project but I would still like to learn about this.

The project I created is available on GitHub and can be found here if you would like to see. There's also a deployed version of the system and can be found here.

Thanks for the help in advance.

mommi84 added a commit that referenced this issue Mar 29, 2021
Update build_vocab.py on python3
mommi84 added a commit that referenced this issue Mar 31, 2021
Update build_vocab.py on python3
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