Demeester, T;
Rocktäschel, T;
Riedel, S;
(2016)
Lifted Rule Injection for Relation Embeddings.
In: Su, J and Duh, K and Carreras, X, (eds.)
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing.
(pp. pp. 1389-1399).
Association for Computational Linguistics/Curran Associates
Preview |
Text
1606.08359v2.pdf - Published Version Download (574kB) | Preview |
Abstract
Methods based on representation learning currently hold the state-of-the-art in many natural language processing and knowledge base inference tasks. Yet, a major challenge is how to efficiently incorporate commonsense knowledge into such models. A recent approach regularizes relation and entity representations by propositionalization of first-order logic rules. However, propositionalization does not scale beyond domains with only few entities and rules. In this paper we present a highly efficient method for incorporating implication rules into distributed representations for automated knowledge base construction. We map entity-tuple embeddings into an approximately Boolean space and encourage a partial ordering over relation embeddings based on implication rules mined from WordNet. Surprisingly, we find that the strong restriction of the entity-tuple embedding space does not hurt the expressiveness of the model and even acts as a regularizer that improves generalization. By incorporating few commonsense rules, we achieve an increase of 2 percentage points mean average precision over a matrix factorization baseline, while observing a negligible increase in runtime.
Type: | Proceedings paper |
---|---|
Title: | Lifted Rule Injection for Relation Embeddings |
Event: | EMNLP 2016, Conference on Empirical Methods in Natural Language Processing, 1-5 November 2016, Austin, Texas |
ISBN-13: | 9781945626258 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.18653/v1/D16-1146 |
Publisher version: | https://aclanthology.coli.uni-saarland.de/papers/D... |
Language: | English |
Additional information: | This is the published version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/1527366 |
1. | United States | 9 |
2. | Russian Federation | 2 |
3. | China | 2 |
4. | Latvia | 1 |
Archive Staff Only
View Item |