Abstract
This demo deals with the problem of capturing omitted arguments in relation extraction given a proper knowledge base for entities of interest. This paper introduces the concept of a salient entity and use this information to deduce omitted entities in the paragraph which allows improving the relation extraction quality. The main idea to compute salient entities is to construct a graph on the given information (by identifying the entities but without parsing it), rank it with standard graph measures and embed it in the context of the sentences.- Anthology ID:
- C18-2011
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico
- Editor:
- Dongyan Zhao
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 48–52
- Language:
- URL:
- https://aclanthology.org/C18-2011
- DOI:
- Cite (ACL):
- Eun-kyung Kim, Kijong Han, Jiho Kim, and Key-Sun Choi. 2018. Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 48–52, Santa Fe, New Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs (Kim et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/C18-2011.pdf