Abstract
Mention detection is an important preprocessing step for annotation and interpretation in applications such as NER and coreference resolution, but few stand-alone neural models have been proposed able to handle the full range of mentions. In this work, we propose and compare three neural network-based approaches to mention detection. The first approach is based on the mention detection part of a state of the art coreference resolution system; the second uses ELMO embeddings together with a bidirectional LSTM and a biaffine classifier; the third approach uses the recently introduced BERT model. Our best model (using a biaffine classifier) achieves gains of up to 1.8 percentage points on mention recall when compared with a strong baseline in a HIGH RECALL coreference annotation setting. The same model achieves improvements of up to 5.3 and 6.2 p.p. when compared with the best-reported mention detection F1 on the CONLL and CRAC coreference data sets respectively in a HIGH F1 annotation setting. We then evaluate our models for coreference resolution by using mentions predicted by our best model in start-of-the-art coreference systems. The enhanced model achieved absolute improvements of up to 1.7 and 0.7 p.p. when compared with our strong baseline systems (pipeline system and end-to-end system) respectively. For nested NER, the evaluation of our model on the GENIA corpora shows that our model matches or outperforms state-of-the-art models despite not being specifically designed for this task.- Anthology ID:
- 2020.lrec-1.1
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1–10
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.1
- DOI:
- Cite (ACL):
- Juntao Yu, Bernd Bohnet, and Massimo Poesio. 2020. Neural Mention Detection. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1–10, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Neural Mention Detection (Yu et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.lrec-1.1.pdf
- Code
- juntaoy/dali-md
- Data
- CoNLL-2012