Newsreader at semeval-2018 task 5: counting events by reasoning over event-centric-knowledge-graphs

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper, we describe the participation of the NewsReader system in the SemEval-2018 Task 5 on Counting Events and Participants in the Long Tail. NewsReader is a generic unsupervised text processing system that detects events with participants, time and place to generate Event Centric Knowledge Graphs (ECKGs). We minimally adapted these ECKGs to establish a baseline performance for the task. We first use the ECKGs to establish which documents report on the same incident and what event mentions are coreferential. Next, we aggregate ECKGs across coreferential mentions and use the aggregated knowledge to answer the questions of the task. Our participation tests the quality of NewsReader to create ECKGs, as well as the potential of ECKGs to establish event identity and reason over the result to answer the task queries.
Original languageEnglish
Title of host publicationProceedings of the 12th International Workshop on Semantic Evaluation
PublisherAssociation for Computational Linguistics
Pages660-666
Number of pages7
DOIs
Publication statusPublished - 2018
Event12th International Workshop on Semantic Evaluation SemEval 2018 - New Orleans
Duration: 23 Apr 2018 → …
Conference number: 12

Conference

Conference12th International Workshop on Semantic Evaluation SemEval 2018
Abbreviated titleSemEval 2018
CityNew Orleans
Period23/04/18 → …

Fingerprint

Dive into the research topics of 'Newsreader at semeval-2018 task 5: counting events by reasoning over event-centric-knowledge-graphs'. Together they form a unique fingerprint.

Cite this