Title: HiEve: A corpus for extracting event hierarchies from news stories
Authors: Glavaš, Goran
Šnajder, Jan
Kordjamshidi, Parisa
Moens, Marie-Francine
Issue Date: 2014
Publisher: ELRA
Host Document: Proceedings of 9th language resources and evaluation conference pages:3678-3683
Conference: 9th language resources and evaluation conference location:Reykjavik, Iceland date:26-31 May 2014
Abstract: Narratives in news stories typically describe a real-world event of coarse spatial and temporal granularity along with its subevents. In this work, we present HiEve, a corpus for recognizing relations of spatiotemporal containment between events. In HiEve, the narratives are represented as hierarchies of events based on relations of spatiotemporal containment (i.e., superevent–subevent relations). We describe the process of manual
annotation of HiEve. Furthermore, we build a supervised classifier for recognizing spatiotemporal containment between events to serve
as a baseline for future research. Preliminary experimental results are encouraging, with classifier performance reaching 58% F1-score,
only 11% less than the inter-annotator agreement.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section

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