Semantic Web Dog Food

Presented at: The Sixth International Language Resources and Evaluation Conference (LREC2008)

by Claire Cardie, Cynthia Farina, Matt Rawding, Adil Aijaz

We describe the creation of a corpus that supports a real-world hierarchical text categorization task in the domain of electronic rulemaking (eRulemaking). Features of the task and of the eRulemaking domain engender both a non-traditional text categorization corpus and a correspondingly difficult machine learning task. Interannotator agreement results are presented for a group of six annotators. We also briefly describe the results of experiments that apply standard and hierarchical text categorization techniques to the eRulemaking data sets. The corpus is the first in a series of related sentence-level text categorization corpora to be developed in the eRulemaking domain.

Keywords: Corpus (creation, annotation, etc.), Document Classification, Text categorisation, LR national/international projects, organizational/policy issues, Linguistics

Resource URI on the dog food server: http://data.semanticweb.org/conference/lrec/2008/papers/699

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