Enriching Frame Representations with Distributionally Induced Senses
Abstract
We introduce a new lexical resource that enriches the Framester knowledge graph, which links Framnet, WordNet, VerbNet and other resources, with semantic features from text corpora. These features are extracted from distributionally induced sense inventories and subsequently linked to the manually-constructed frame representations to boost the performance of frame disambiguation in context. Since Framester is a frame-based knowledge graph, which enables full-fledged OWL querying and reasoning, our resource paves the way for the development of novel, deeper semantic-aware applications that could benefit from the combination of knowledge from text and complex symbolic representations of events and participants. Together with the resource we also provide the software we developed for the evaluation in the task of Word Frame Disambiguation (WFD).
Cite
@article{arxiv.1803.05829,
title = {Enriching Frame Representations with Distributionally Induced Senses},
author = {Stefano Faralli and Alexander Panchenko and Chris Biemann and Simone Paolo Ponzetto},
journal= {arXiv preprint arXiv:1803.05829},
year = {2018}
}
Comments
In Proceedings of the 11th Conference on Language Resources and Evaluation (LREC 2018). Miyazaki, Japan. ELRA