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- W2002772726 abstract "Automatic reading comprehension (RC) systems can analyze a given passage and generate/extract answers in response to questions about the passage. The RC passages are often constrained in their lengths and the target answer sentence usually occurs very few times. In order to generate/extract a specific precise answer, this paper proposes the integration of two types of deep linguistic features, namely word dependencies and grammatical relations, in a maximum entropy (ME) framework to handle the RC task. The proposed approach achieves 44.7% and 73.2% HumSent accuracy on the Remedia and ChungHwa corpora respectively. This result is competitive with other results reported thus far." @default.
- W2002772726 created "2016-06-24" @default.
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- W2002772726 date "2006-01-01" @default.
- W2002772726 modified "2023-10-14" @default.
- W2002772726 title "A maximum entropy framework that integrates word dependencies and grammatical relations for reading comprehension" @default.
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- W2002772726 doi "https://doi.org/10.3115/1614049.1614096" @default.
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