Details

Autor(en) / Beteiligte

• Gliozzo, Alfio Massimiliano
• Kalyanpur, Aditya

Titel

Predicting Lexical Answer Types in Open Domain QA

Ist Teil von

• International journal on semantic web and information systems, 2012-07, Vol.8 (3), p.74-88

Ort / Verlag

Hershey: IGI Global

Erscheinungsjahr

2012

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Automatic open-domain Question Answering has been a long standing research challenge in the AI community. IBM Research undertook this challenge with the design of the DeepQA architecture and the implementation of Watson. This paper addresses a specific subtask of Deep QA, consisting of predicting the Lexical Answer Type (LAT) of a question. Our approach is completely unsupervised and is based on PRISMATIC, a large-scale lexical knowledge base automatically extracted from a Web corpus. Experiments on the Jeopardy! data shows that it is possible to correctly predict the LAT in a substantial number of questions. This approach can be used for general purpose knowledge acquisition tasks such as frame induction from text.