4 and 7-bit Labeling for Projective and Non-Projective Dependency Trees

October 22, 2023 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Carlos Gรณmez-Rodrรญguez, Diego Roca, David Vilares arXiv ID 2310.14319 Category cs.CL: Computation & Language Cross-listed cs.FL Citations 7 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 5 months ago
Abstract
We introduce an encoding for parsing as sequence labeling that can represent any projective dependency tree as a sequence of 4-bit labels, one per word. The bits in each word's label represent (1) whether it is a right or left dependent, (2) whether it is the outermost (left/right) dependent of its parent, (3) whether it has any left children and (4) whether it has any right children. We show that this provides an injective mapping from trees to labels that can be encoded and decoded in linear time. We then define a 7-bit extension that represents an extra plane of arcs, extending the coverage to almost full non-projectivity (over 99.9% empirical arc coverage). Results on a set of diverse treebanks show that our 7-bit encoding obtains substantial accuracy gains over the previously best-performing sequence labeling encodings.
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