Abstract
In this paper we present BabelDomains, a unified resource which provides lexical items with information about domains of knowledge. We propose an automatic method that uses knowledge from various lexical resources, exploiting both distributional and graph-based clues, to accurately propagate domain information. We evaluate our methodology intrinsically on two lexical resources (WordNet and BabelNet), achieving a precision over 80% in both cases. Finally, we show the potential of BabelDomains in a supervised learning setting, clustering training data by domain for hypernym discovery.- Anthology ID:
- E17-2036
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 223–228
- Language:
- URL:
- https://aclanthology.org/E17-2036
- DOI:
- Cite (ACL):
- Jose Camacho-Collados and Roberto Navigli. 2017. BabelDomains: Large-Scale Domain Labeling of Lexical Resources. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 223–228, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- BabelDomains: Large-Scale Domain Labeling of Lexical Resources (Camacho-Collados & Navigli, EACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/E17-2036.pdf