Answer Extraction for Question Answering Game Application
نویسندگان
چکیده
The paper presents an approach to answer extraction for a Question Answering Dialogue System (QADS), which is a part of an interactive quiz game. The information that forms the content of this game is concerned with biographical facts of famous people’s life. The facts are extracted from Wikipedia pages by means of semantic relations, whose fillers are identified by trained sequence classifiers and pattern matching tools, and edited to be returned to the player as full-fledged system answers. The overall average F-score of 0.66 has been achieved, where for separate semantic relations F-score ranges from 0.21 to 0.90. The reported results show that the presented approach fits the data well and can be considered as a promising method for other QA domains, in particular when dealing with unstructured information.
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