Abstract
We develop CALM, a coordination analyzer that improves upon the conjuncts identified from dependency parses. It uses a language model based scoring and several linguistic constraints to search over hierarchical conjunct boundaries (for nested coordination). By splitting a conjunctive sentence around these conjuncts, CALM outputs several simple sentences. We demonstrate the value of our coordination analyzer in the end task of Open Information Extraction (Open IE). State-of-the-art Open IE systems lose substantial yield due to ineffective processing of conjunctive sentences. Our Open IE system, CALMIE, performs extraction over the simple sentences identified by CALM to obtain up to 1.8x yield with a moderate increase in precision compared to extractions from original sentences.- Anthology ID:
- C18-1194
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2288–2299
- Language:
- URL:
- https://aclanthology.org/C18-1194
- DOI:
- Cite (ACL):
- Swarnadeep Saha and Mausam. 2018. Open Information Extraction from Conjunctive Sentences. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2288–2299, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Open Information Extraction from Conjunctive Sentences (Saha & Mausam, COLING 2018)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/C18-1194.pdf
- Data
- CaRB