SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings
Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Ido Dagan, Yoav Goldberg, Alon Eirew, Yael Green, Shira Guskin, Peter Izsak, Daniel Korat
Abstract
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 .- Anthology ID:
- C18-2013
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 58–62
- Language:
- URL:
- https://www.aclweb.org/anthology/C18-2013
- DOI:
- PDF:
- http://aclanthology.lst.uni-saarland.de/C18-2013.pdf