The Event StoryLine Corpus: A new Benchmark for causal and temporal Relation Extraction

T. Caselli, P.T.J.M. Vossen

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


This paper reports on the Event StoryLine Corpus (ESC) v1.0, a new benchmark dataset for the temporal and causal relation detection. By developing this dataset, we also introduce a new task, the StoryLine Extraction from news data, which aims at extracting and classifying events relevant for stories, from across news documents spread in time and clustered around a single seminal event or topic. In addition to describing the dataset, we also report on three baselines systems whose results show the complexity of the task and suggest directions for the development of more robust systems.
Original languageEnglish
Title of host publicationProceedings of the workshop Events and Stories in the News
PublisherACL Anthology
Number of pages10
Publication statusPublished - 2017

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