Summary of the paper

Title Building a Gold Standard for Event Detection in Croatian
Authors Nikola Ljubešić, Tomislava Lauc and Damir Boras
Abstract This paper describes the process of building a newspaper corpus annotated with events described in specific documents. The main difference to the corpora built as part of the TDT initiative is that documents are not annotated by topics, but by specific events they describe. Additionally, documents are gathered from sixteen sources and all documents in the corpus are annotated with the corresponding event. The annotation process consists of a browsing and a searching step. Experiments are performed with a threshold that could be used in the browsing step yielding the result of having to browse through only 1% of document pairs for a 2% loss of relevant document pairs. A statistical analysis of the annotated corpus is undertaken showing that most events are described by few documents while just some events are reported by many documents. The inter-annotator agreement measures show high agreement concerning grouping documents into event clusters, but show a much lower agreement concerning the number of events the documents are organized into. An initial experiment is described giving a baseline for further research on this corpus.
Topics Topic detection & tracking, Evaluation methodologies, Document Classification, Text categorisation
Full paper Building a Gold Standard for Event Detection in Croatian
Slides -
Bibtex @InProceedings{LJUBEI10.213,
  author = {Nikola Ljubešić and Tomislava Lauc and Damir Boras},
  title = {Building a Gold Standard for Event Detection in Croatian},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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