N Semantic Classes are Harder than Two

We show that we can automatically classify semantically related phrases into 10 classes. Classification robustness is improved by training with multiple sources of evidence, including within-document cooccurrence, HTML markup, syntactic relationships in sentences, substitutability in query logs, and string similarity. Our work provides a benchmark for automatic n-way classification into WordNet's semantic classes, both on a TREC news corpus and on a corpus of substitutable search query phrases.

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Ben Carterette, Rosie Jones, Wiley Greiner, Cory Barr
• Keywords: ACL 2006, ACL 2007, Automatic N-way Classification, Search Query Phrases, WordNet's Semantic Classes