Paper: A Framework for Entailed Relation Recognition

ACL ID P09-2015
Title A Framework for Entailed Relation Recognition
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

We define the problem of recognizing entailed re- lations – given an open set of relations, find all oc- currences of the relations of interest in a given doc- ument set – and pose it as a challenge to scalable information extraction and retrieval. Existing ap- proaches to relation recognition do not address well problems with an open set of relations and a need for high recall: supervised methods are not eas- ily scaled, while unsupervised and semi-supervised methods address a limited aspect of the problem, as they are restricted to frequent, explicit, highly lo- calized patterns. We argue that textual entailment (TE) is necessary to solve such problems, propose a scalable TE architecture, and provide preliminary results on an Entailed Relation Recognition task.