On Coreferring Text-extracted Event Descriptions with the aid of Ontological Reasoning

TL;DR

This paper presents a novel method for event coreference resolution that leverages ontological reasoning and semantic rules on text-extracted event data, improving accuracy by incorporating event type properties.

Contribution

It introduces a formal ontological analysis of event types and implements RDF-based reasoning rules for coreference, advancing event recognition techniques.

Findings

Effective coreference resolution using ontological reasoning.

Improved accuracy on benchmark datasets.

Formal analysis of event ontological properties.

Abstract

Systems for automatic extraction of semantic information about events from large textual resources are now available: these tools are capable to generate RDF datasets about text extracted events and this knowledge can be used to reason over the recognized events. On the other hand, text based tasks for event recognition, as for example event coreference (i.e. recognizing whether two textual descriptions refer to the same event), do not take into account ontological information of the extracted events in their process. In this paper, we propose a method to derive event coreference on text extracted event data using semantic based rule reasoning. We demonstrate our method considering a limited (yet representative) set of event types: we introduce a formal analysis on their ontological properties and, on the base of this, we define a set of coreference criteria. We then implement these criteria as RDF-based reasoning rules to be applied on text extracted event data. We evaluate the effectiveness of our approach over a standard coreference benchmark dataset.