Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Consistent CCG Parsing over Multiple Sentences for Improved Logical
  Reasoning   In formal logic-based approaches to Recognizing Textual Entailment (RTE), a
Combinatory Categorial Grammar (CCG) parser is used to parse input premises and
hypotheses to obtain their logical formulas. Here, it is important that the
parser processes the sentences consistently; failing to recognize a similar
syntactic structure results in inconsistent predicate argument structures among
them, in which case the succeeding theorem proving is doomed to failure. In
this work, we present a simple method to extend an existing CCG parser to parse
a set of sentences consistently, which is achieved with an inter-sentence
modeling with Markov Random Fields (MRF). When combined with existing
logic-based systems, our method always shows improvement in the RTE experiments
on English and Japanese languages.

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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: solv-int
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The categories of this paper are: eess
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The categories of this paper are: gr-qc
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-ex
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The categories of this paper are: hep-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: plasm-ph
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex
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The categories of this paper are: quant-ph
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg