Enriching Frame Representations with Distributionally Induced Senses

TL;DR

This paper presents a new lexical resource that enhances a frame knowledge graph with distributionally induced senses from text, improving frame disambiguation and enabling advanced semantic applications.

Contribution

It introduces a novel resource linking sense inventories to frame representations in Framester, facilitating better disambiguation and reasoning in semantic applications.

Findings

Improved performance in Word Frame Disambiguation tasks

Enhanced semantic reasoning capabilities with the enriched resource

Open-source software for evaluation provided

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).