Paper: Probabilistic Soft Logic for Semantic Textual Similarity

ACL ID P14-1114
Title Probabilistic Soft Logic for Semantic Textual Similarity
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Probabilistic Soft Logic (PSL) is a re- cently developed framework for proba- bilistic logic. We use PSL to combine logical and distributional representations of natural-language meaning, where distri- butional information is represented in the form of weighted inference rules. We ap- ply this framework to the task of Seman- tic Textual Similarity (STS) (i.e. judg- ing the semantic similarity of natural- language sentences), and show that PSL gives improved results compared to a pre- vious approach based on Markov Logic Networks (MLNs) and a purely distribu- tional approach.