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Analysis of the Effect of Dependency Information on Predicate-Argument Structure Analysis and Zero Anaphora Resolution

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Koichiro Yoshino, Shinsuke Mori, Satoshi Nakamura

Computation and Language · Submitted 31 May 2017

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim This paper investigates and analyzes the effect of dependency information on predicate-argument structure analysis (PASA) and zero anaphora resolution (ZAR) for Japanese, and shows that a straightforward approach of PASA and ZAR works effectively even if dependency information was not available.

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arXiv ID1705.10962 (version 1)
Pith IDTIIRVXOU, Pith's permanent record of this paper and its review
CitationKoichiro Yoshino, Satoshi Nakamura, Shinsuke Mori. "Analysis of the Effect of Dependency Information on Predicate-Argument Structure Analysis and Zero Anaphora Resolution." arXiv:1705.10962 (2017). https://pith.science/paper/TIIRVXOU
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,689 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.47 · human participants 0.02 · controlled comparison 0.93 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.89 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

This paper investigates and analyzes the effect of dependency information on predicate-argument structure analysis (PASA) and zero anaphora resolution (ZAR) for Japanese, and shows that a straightforward approach of PASA and ZAR works effectively even if dependency information was not available. We constructed an analyzer that directly predicts relationships of predicates and arguments with their semantic roles from a POS-tagged corpus. The features of the system are designed to compensate for the absence of syntactic information by using features used in dependency parsing as a reference. We also constructed analyzers that use the oracle dependency and the real dependency parsing results, and compared with the system that does not use any syntactic information to verify that the improvement provided by dependencies is not crucial.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 This paper investigates and analyzes the effect of dependency information on predicate-argument structure analysis (PASA) and zero anaphora resolution (ZAR) for Japanese, and shows that a straightforward approach of PASA and ZAR works effectively even if dependency information was not available. result 0.55 0.94 0.93 asserted 1.00
s1 We constructed an analyzer that directly predicts relationships of predicates and arguments with their semantic roles from a POS-tagged corpus. method 0.97 0.96 0.03 asserted 0.98
s2 The features of the system are designed to compensate for the absence of syntactic information by using features used in dependency parsing as a reference. method 0.99 0.86 0.04 asserted 0.97
s3 We also constructed analyzers that use the oracle dependency and the real dependency parsing results, and compared with the system that does not use any syntactic information to verify that the improvement provided by dependencies is not crucial. method 0.67 0.96 0.38 asserted 0.99

What kind of paper the classifier reports this is: empirical study 0.90 · evidence from observation or experiment 0.89.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

This paper investigates and analyzes the effect of dependency information on predicate-argument structure analysis (PASA) and zero anaphora resolution (ZAR) for Japanese, and shows that a straightforward approach of PASA and ZAR works effectively even if dependency information was not available. We constructed an analyzer that directly predicts relationships of predicates and arguments with their semantic roles from a POS-tagged corpus. The features of the system are designed to compensate for the absence of syntactic information by using features used in dependency parsing as a reference. We also constructed analyzers that use the oracle dependency and the real dependency parsing results, and compared with the system that does not use any syntactic information to verify that the improvement provided by dependencies is not crucial.

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