HiEve: A Corpus for Extracting Event Hierarchies from News Stories (CROSBI ID 613523)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Glavaš, Goran ; Šnajder, Jan ; Moens ; Marie-Francine Moens ; Kordjamshidi, Parisa
engleski
HiEve: A Corpus for Extracting Event Hierarchies from News Stories
In news stories, event mentions denote real-world events of different spatial and temporal granularity. Narratives in news stories typically describe some 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.
Event hierarchies; spatiotemporal containment; relation extraction
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Podaci o prilogu
3678-3683.
2014.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Reykjavík: European Language Resources Association (ELRA)
Podaci o skupu
The Ninth International Conference on Language Resources and Evaluation (LREC'14)
poster
26.05.2014-31.05.2014
Reykjavík, Island