lexical knowledge base
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ETRI Journal ◽  
2017 ◽  
Vol 39 (2) ◽  
pp. 191-201 ◽  
Author(s):  
Jeong Heo ◽  
Hyung-Jik Lee ◽  
Ji-Hyun Wang ◽  
Yong-Jin Bae ◽  
Hyun-Ki Kim ◽  
...  

Author(s):  
Alfio Massimiliano Gliozzo ◽  
Aditya Kalyanpur

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.


Author(s):  
Francisco J. Carreras-Riudavets ◽  
Juan C. Rodríguez-del-Pino ◽  
Zenón Hernández-Figueroa ◽  
Gustavo Rodríguez-Rodríguez

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