Mining the web for reciprocal relationships

Michael Paul, Roxana Girju, Chen Li

Research output: Contribution to conferencePaperpeer-review


In this paper we address the problem of identifying reciprocal relationships in English. In particular we introduce an algorithm that semi-automatically discovers patterns encoding reciprocity based on a set of simple but effective pronoun templates. Using a set of most frequently occurring patterns, we extract pairs of reciprocal pattern instances by searching the web. Then we apply two unsupervised clustering procedures to form meaningful clusters of such reciprocal instances. The pattern discovery procedure yields an accuracy of 97%, while the clustering procedures indicate accuracies of 91% and 82%. Moreover, the resulting set of 10,882 reciprocal instances represent a broad-coverage resource.

Original languageEnglish (US)
StatePublished - Jun 2009
Event13th Conference on Computational Natural Language Learning, CoNLL 2009 - Boulder, CO, United States
Duration: Jun 4 2009Jun 5 2009


Other13th Conference on Computational Natural Language Learning, CoNLL 2009
Country/TerritoryUnited States
CityBoulder, CO

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language


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