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EMNLP 2023mainmain

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

Carlos Gómez-Rodríguez, Diego Roca, David Vilares

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2023.emnlp-main.393 ↗

摘要

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.