TL;DR
This paper introduces a bracketing-based encoding for 2-planar dependency trees that significantly improves non-projective parsing accuracy by leveraging the property that most syntactic structures are 2-planar, enabling near-complete coverage of crossing arcs.
Contribution
The authors develop a novel bracketing encoding that handles almost all 2-planar dependency trees, overcoming previous limitations and enhancing sequence labeling parsing for non-projective structures.
Findings
Achieves around 99.9% coverage of crossing arcs in 2-planar trees.
Improves LAS by approximately 0.4 points on highly non-projective treebanks.
Maintains similar parsing speed to previous encodings.
Abstract
We present a bracketing-based encoding that can be used to represent any 2-planar dependency tree over a sentence of length n as a sequence of n labels, hence providing almost total coverage of crossing arcs in sequence labeling parsing. First, we show that existing bracketing encodings for parsing as labeling can only handle a very mild extension of projective trees. Second, we overcome this limitation by taking into account the well-known property of 2-planarity, which is present in the vast majority of dependency syntactic structures in treebanks, i.e., the arcs of a dependency tree can be split into two planes such that arcs in a given plane do not cross. We take advantage of this property to design a method that balances the brackets and that encodes the arcs belonging to each of those planes, allowing for almost unrestricted non-projectivity (round 99.9% coverage) in sequence…
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