An Attentive Fine-Grained Entity Typing Model with Latent Type Representation

Ying Lin, Heng Ji

Abstract
We propose a fine-grained entity typing model with a novel attention mechanism and a hybrid type classifier. We advance existing methods in two aspects: feature extraction and type prediction. To capture richer contextual information, we adopt contextualized word representations instead of fixed word embeddings used in previous work. In addition, we propose a two-step mention-aware attention mechanism to enable the model to focus on important words in mentions and contexts. We also present a hybrid classification method beyond binary relevance to exploit type inter-dependency with latent type representation. Instead of independently predicting each type, we predict a low-dimensional vector that encodes latent type features and reconstruct the type vector from this latent representation. Experiment results on multiple data sets show that our model significantly advances the state-of-the-art on fine-grained entity typing, obtaining up to 6.1% and 5.5% absolute gains in macro averaged F-score and micro averaged F-score respectively.
Anthology ID:
D19-1641
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
6197–6202
Language:
URL:
https://preview.aclanthology.org/remove-affiliations/D19-1641/
DOI:
10.18653/v1/D19-1641
Bibkey:
Cite (ACL):
Ying Lin and Heng Ji. 2019. An Attentive Fine-Grained Entity Typing Model with Latent Type Representation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 6197–6202, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
An Attentive Fine-Grained Entity Typing Model with Latent Type Representation (Lin & Ji, EMNLP-IJCNLP 2019)
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https://preview.aclanthology.org/remove-affiliations/D19-1641.pdf
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