@inproceedings{bensley-hickl-2008-unsupervised,
    title = "Unsupervised Resource Creation for Textual Inference Applications",
    author = "Bensley, Jeremy  and
      Hickl, Andrew",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Odijk, Jan  and
      Piperidis, Stelios  and
      Tapias, Daniel",
    booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
    month = may,
    year = "2008",
    address = "Marrakech, Morocco",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/fix-sig-urls/L08-1224/",
    abstract = "This paper explores how a battery of unsupervised techniques can be used in order to create large, high-quality corpora for textual inference applications, such as systems for recognizing textual entailment (TE) and textual contradiction (TC). We show that it is possible to automatically generate sets of positive and negative instances of textual entailment and contradiction from textual corpora with greater than 90{\%} precision. We describe how we generated more than 1 million TE pairs - and a corresponding set of and 500,000 TC pairs - from the documents found in the 2 GB AQUAINT-2 newswire corpus."
}