In this paper we describe a method to detect event descriptions in different news articles and to model the semantics of events and their components using RDF representations. We compare these descriptions to solve a cross-document event coreference task. Our component approach to event semantics defines identity and granularity of events at different levels. It performs close to state-of-the-art approaches on the cross-document event coreference task, while outperforming other works when assuming similar quality of event detection. We demonstrate how granularity and identity are interconnected and we discuss how semantic anomaly could be used to define differences between coreference, subevent and topical relations
Event coreference resolution is a task in which different text fragments that refer to the same real...
We have studied several techniques for creating and comparing content represen-tations of textual do...
Collateral texts of different genre can describe the same filmed story, e.g. audio description and p...
Recently, systems for automatic extraction of semantic information about events from large textual r...
Systems for automatic extraction of semantic information about events from large textual resources a...
Event coreference detection is a task of automatically determining which fine-grained textual descri...
We investigate the novel problem of event recognition from news webpages. "Events" are bas...
Event coreference resolution aims to determine and cluster event mentions that refer to the same rea...
A simple conceptual model is employed to investigate events, and break the task of coreference resol...
Event coreference is an important task for full text analysis. However, previous work uses a variety...
We describe a system for event extraction across documents and languages. We devel-oped a framework ...
This paper is about a new type of event database that enables efficient reasoning about things, peop...
Abstract. In this study we look at new requirements for event models based on concepts defined for c...
The task of event coreference resolution plays a critical role in many natural language pro-cessing ...
In this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool ...
Event coreference resolution is a task in which different text fragments that refer to the same real...
We have studied several techniques for creating and comparing content represen-tations of textual do...
Collateral texts of different genre can describe the same filmed story, e.g. audio description and p...
Recently, systems for automatic extraction of semantic information about events from large textual r...
Systems for automatic extraction of semantic information about events from large textual resources a...
Event coreference detection is a task of automatically determining which fine-grained textual descri...
We investigate the novel problem of event recognition from news webpages. "Events" are bas...
Event coreference resolution aims to determine and cluster event mentions that refer to the same rea...
A simple conceptual model is employed to investigate events, and break the task of coreference resol...
Event coreference is an important task for full text analysis. However, previous work uses a variety...
We describe a system for event extraction across documents and languages. We devel-oped a framework ...
This paper is about a new type of event database that enables efficient reasoning about things, peop...
Abstract. In this study we look at new requirements for event models based on concepts defined for c...
The task of event coreference resolution plays a critical role in many natural language pro-cessing ...
In this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool ...
Event coreference resolution is a task in which different text fragments that refer to the same real...
We have studied several techniques for creating and comparing content represen-tations of textual do...
Collateral texts of different genre can describe the same filmed story, e.g. audio description and p...