Entailment above the word level in distributional semantics

Author

Baroni, Marco and Bernardi, Raffaella and Do, Ngoc-Quynh and Shan, Chung-chieh

Conference

Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

Year

2012

Figures & Tables

Table 3: Detecting quantifier entailment. Results ranked by accuracy and expressed as percentages.95% confidence intervals around accuracy calculated by binomial exact tests.
Table 1: Entailing and non-entailing quantifier pairs with number of instances per pair (Section 3.4) and SVM pair-out performance breakdown (Section 5).
Table 4: Breakdown of results with leaving-one-quantifier-out (SVM quantifier-out ) training regime.
Table 2: Detecting lexical entailment. Results ranked by accuracy and expressed as percentages. 95% confidence intervals around accuracy calculated by binomial exact tests.

Table of Contents

  • Abstract lexical domain. On the other hand, FS has pro-
  • 2 Background
    • 2.1 Distributional semantics above the word level
    • 2.2 Entailment from formal to distributional semantics
  • 3 Data and methods
    • 3.1 Semantic space
    • 3.2 The AN |= N data set
    • 3.3 The lexical entailment N 1 |= N 2 data set
    • 3.4 The Q 1 N |= Q 2 N data set
    • 3.5 Classification methods
  • 4 Predicting lexical entailment from AN |= N evidence
  • 5 Generalizing QN entailment
  • 6 Conclusion
  • Acknowledgments
  • References

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