Summary of the paper

Title Semantic Role Labeling with the Swedish FrameNet
Authors Richard Johansson, Karin Friberg Heppin and Dimitrios Kokkinakis
Abstract We present the first results on semantic role labeling using the Swedish FrameNet, which is a lexical resource currently in development. Several aspects of the task are investigated, including the %design and selection of machine learning features, the effect of choice of syntactic parser, and the ability of the system to generalize to new frames and new genres. In addition, we evaluate two methods to make the role label classifier more robust: cross-frame generalization and cluster-based features. Although the small amount of training data limits the performance achievable at the moment, we reach promising results. In particular, the classifier that extracts the boundaries of arguments works well for new frames, which suggests that it already at this stage can be useful in a semi-automatic setting.
Topics Semantics, Lexicon, lexical database, Information Extraction, Information Retrieval
Full paper Semantic Role Labeling with the Swedish FrameNet
Bibtex @InProceedings{JOHANSSON12.455,
  author = {Richard Johansson and Karin Friberg Heppin and Dimitrios Kokkinakis},
  title = {Semantic Role Labeling with the Swedish FrameNet},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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