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the claim

Addressing syntactic discontinuity and nonprojectivity is important for computational parsing

the verdict
SUPPORTED
the evidence backs this
Recorded sources
7 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that addressing syntactic discontinuity and nonprojectivity is important for computational parsing?

Yes. Computational studies consistently demonstrate that addressing syntactic discontinuity and nonprojectivity is essential for accurate and efficient dependency parsing.

Verdict: SUPPORTED · 7 sources for, 0 against · Last checked

The analysis

The retrieved papers ([0], [1], [2], [3], [7], [9], [10]) specifically focus on developing and evaluating parsing algorithms for non-projective and discontinuous structures, showing that handling nonprojectivity is important for improving both accuracy and efficiency in computational parsing. There are no papers refuting this claim.

Evidence for · 7
Non-Projective Dependency Parsing using Spanning Tree Algorithms
2005
Demonstrates that modeling non-projective dependencies increases parsing efficiency and accuracy for languages containing them.
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McDonald, R. T., Pereira, F. C., Ribarov, K., & Hajic, J. (2005). Non-Projective Dependency Parsing using Spanning Tree Algorithms. doi.org. https://doi.org/10.3115/1220575.1220641

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More for · 6
Algorithms for Deterministic Incremental Dependency Parsing
2008
Shows that non-projective dependency parsing algorithms outperform projective ones in languages with significant non-projective constructions.
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Nivre, J. (2008). Algorithms for Deterministic Incremental Dependency Parsing. doi.org. https://doi.org/10.1162/coli.07-056-R1-07-027

Non-Projective Dependency Parsing in Expected Linear Time
2009
Presents efficient transition systems designed specifically to parse arbitrary non-projective trees with state-of-the-art accuracy.
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Nivre, J. (2009). Non-Projective Dependency Parsing in Expected Linear Time. doi.org. https://doi.org/10.3115/1687878.1687929

On the Complexity of Non-Projective Data-Driven Dependency Parsing
2007
Investigates polynomial-time parsing algorithms for non-projective data-driven dependency parsing.
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McDonald, R. T. & Satta, G. (2007). On the Complexity of Non-Projective Data-Driven Dependency Parsing. doi.org. https://doi.org/10.3115/1621410.1621426

Parsing Mildly Non-Projective Dependency Structures
2009
Develops parsing algorithms specifically tailored for mildly non-projective dependency structures present in treebanks.
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Gómez-Rodríguez, C., Weir, D. J., & Carroll, J. A. (2009). Parsing Mildly Non-Projective Dependency Structures. doi.org. https://doi.org/10.3115/1609067.1609099

Dependency Parsing Schemata and Mildly Non-Projective Dependency Parsing
2011
Introduced parsing schemata that describe and analyze new polynomial-time parsing algorithms for mildly non-projective formalisms.
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Gómez-Rodríguez, C., Carroll, J., & Weir, D. (2011). Dependency Parsing Schemata and Mildly Non-Projective Dependency Parsing. doi.org. https://doi.org/10.1162/coli_a_00060

Hybrid Grammars for Parsing of Discontinuous Phrase Structures and Non-Projective Dependency Structures
2017
Explores hybrid grammars designed to handle discontinuous phrase structures and non-projective dependency structures in parsing.
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Gebhardt, K., Nederhof, M., & Vogler, H. (2017). Hybrid Grammars for Parsing of Discontinuous Phrase Structures and Non-Projective Dependency Structures. doi.org. https://doi.org/10.1162/COLI_a_00291

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What does the evidence say?

The retrieved papers ([0], [1], [2], [3], [7], [9], [10]) specifically focus on developing and evaluating parsing algorithms for non-projective and discontinuous structures, showing that handling nonprojectivity is important for improving both accuracy and efficiency in computational parsing. There are no papers refuting this claim.

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 9404 Aug 2026
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