Paper: Unsupervised extraction of semantic relations using discourse cues

ACL ID C14-1206
Title Unsupervised extraction of semantic relations using discourse cues
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

This paper presents a knowledge base containing triples involving pairs of verbs associated with semantic or discourse relations. The relations in these triples are marked by discourse connectors between two adjacent instances of the verbs in the triple in the large French corpus, frWaC. We detail several measures that evaluate the relevance of the triples and the strength of their association. We use manual annotations to evaluate our method, and also study the coverage of our resource with respect to the discourse annotated corpus Annodis. Our positive results show the potential impact of our resource for discourse analysis tasks as well as other semantically oriented tasks like temporal and causal information extraction.