Yael Green
2018
SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings
Jonathan Mamou
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Oren Pereg
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Moshe Wasserblat
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Ido Dagan
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Yoav Goldberg
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Alon Eirew
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Yael Green
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Shira Guskin
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Peter Izsak
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Daniel Korat
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to end workflow for term set expansion. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system. A video demo of SetExpander is available at https://drive.google.com/open?id=1e545bB87Autsch36DjnJHmq3HWfSd1Rv .
Term Set Expansion based NLP Architect by Intel AI Lab
Jonathan Mamou
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Oren Pereg
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Moshe Wasserblat
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Alon Eirew
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Yael Green
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Shira Guskin
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Peter Izsak
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Daniel Korat
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to-end workflow. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used successfully in real-life use cases including integration into an automated recruitment system and an issues and defects resolution system.
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Co-authors
- Jonathan Mamou 2
- Oren Pereg 2
- Moshe Wasserblat 2
- Alon Eirew 2
- Shira Guskin 2
- show all...