Abstract
We present a system to acquire knowledge on the activities of people engaged in certain occupations. While most of the previous studies acquire phrases related to the occupation, our system acquires pairs of a verb and one of its arguments, which we call activities. Our system acquires activities from sentences written by people engaged in the target occupations as well as from sentences whose subjects are the target occupations. Through experiments, we show that the activities collected from each resource have different characteristics and the system based on the two resources would perform robustly for various occupations.
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Notes
- 1.
The author-based component extracts the authors’ own activities with the accuracy of 65.0 % by using our rules. This accuracy does not directly affect the performance of the system, because specific activities are finally selected on the basis of \(\chi ^2\) scores.
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- 3.
We used predicate-argument pairs provided by Kawahara and Kurohashi. For details of the method of extracting predicate-argument pairs from a Web corpus, please see Kawahara and Kurohashi [6].
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Less than 100 users are collected for curator, detective, and station staff. Annotators examined all users for them.
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Acknowledgement
We would like to acknowledge Prof. Kurohashi and Prof. Kawahara for providing us with the data of predicate-argument pairs used in the experiments. This work was supported by JSPS KAKENHI Grant Number JP26280080 and the Center of Innovation Program from Japan Science and Technology Agency, JST.
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Matsunagi, M., Sasano, R., Takamura, H., Okumura, M. (2016). Acquiring Activities of People Engaged in Certain Occupations. In: Booth, R., Zhang, ML. (eds) PRICAI 2016: Trends in Artificial Intelligence. PRICAI 2016. Lecture Notes in Computer Science(), vol 9810. Springer, Cham. https://doi.org/10.1007/978-3-319-42911-3_28
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DOI: https://doi.org/10.1007/978-3-319-42911-3_28
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