Phrase and word level strategies for detecting appositions in speech

Appositions are grammatical constructs in which two noun phrases are placed side-by-side, one modifying the other. Detecting them in speech can help extract semantic information useful, for instance, for co-reference resolution and question answering. We compare and combine three approaches: wordlevel and phrase-level classifiers, and a syntactic parser trained to generate appositions. On reference parses, the phrase-level classifier outperforms the other approaches while on automatic parses and ASR output, the combination of the appositiongenerating parser and the word-level classifier works best. An analysis of the system errors reveals that parsing accuracy and world knowledge are very important for this task.