A Survey on Open Information Extraction
Christina Niklaus, Matthias Cetto, André Freitas, Siegfried Handschuh
Abstract
We provide a detailed overview of the various approaches that were proposed to date to solve the task of Open Information Extraction. We present the major challenges that such systems face, show the evolution of the suggested approaches over time and depict the specific issues they address. In addition, we provide a critique of the commonly applied evaluation procedures for assessing the performance of Open IE systems and highlight some directions for future work.- Anthology ID:
- C18-1326
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3866–3878
- Language:
- URL:
- https://aclanthology.org/C18-1326
- DOI:
- Cite (ACL):
- Christina Niklaus, Matthias Cetto, André Freitas, and Siegfried Handschuh. 2018. A Survey on Open Information Extraction. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3866–3878, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- A Survey on Open Information Extraction (Niklaus et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/C18-1326.pdf