Extracting structured data from Web pages
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
GATE: a General Architecture for Text Engineering
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Modeling Common Real-Word Relations Using Triples Extracted from n-Grams
ASWC '09 Proceedings of the 4th Asian Conference on The Semantic Web
Story graphs: Tracking document set evolution using dynamic graphs
Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
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We propose a pipeline for learning event templates from a large corpus of textual news articles. An event template is a machine-usable semantic data structure, in our case a graph, describing a certain event type. Most earthquake news reports, for example, semantically fit the template "x people dead, town y shook, at time z". Such templates can be used as an input for information extraction tasks or automated ontology extension. We also present preliminary results in the form of sample extracted templates from Google News articles.