Summary of the paper

Title Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations
Authors Maria Sukhareva, Judith Eckle-Kohler, Ivan Habernal and Iryna Gurevych
Abstract We present a new large dataset of 12403 context-sensitive verb relations manually annotated via crowdsourcing. These relations capture fine-grained semantic information between verb-centric propositions, such as temporal or entailment relations. We propose a novel semantic verb relation scheme and design a multi-step annotation approach for scaling-up the annotations using crowdsourcing. We employ several quality measures and report on agreement scores. The resulting dataset is available under a permissive CreativeCommons license at www.ukp.tu-darmstadt.de/data/verb-relations/. It represents a valuable resource for various applications, such as automatic information consolidation or automatic summarization.
Topics Corpus (Creation, Annotation, etc.), Crowdsourcing, Textual Entailment and Paraphrasing
Full paper Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations
Bibtex @InProceedings{SUKHAREVA16.494,
  author = {Maria Sukhareva and Judith Eckle-Kohler and Ivan Habernal and Iryna Gurevych},
  title = {Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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