English

A tree interpretation of arc standard dependency derivation

Computation and Language 2026-05-28 v2

Abstract

Arc-standard derivations over projective dependency trees can be interpreted as the incremental construction of lexicalized ordered trees with contiguous yields. Each \textsc{shift}, \textsc{leftarc}, and \textsc{rightarc} transition corresponds to a deterministic tree update, and the resulting ordered tree uniquely determines the dependency arcs introduced by the derivation. We show that this representation is not an arbitrary encoding: a single-headed dependency tree admits such a contiguous ordered representation if and only if it is projective. The proposal is therefore derivational rather than conversion-based, since the ordered object is defined over the transition sequence itself rather than obtained by transforming a completed dependency graph. This gives a tree-theoretic interpretation of arc-standard parsing, in which projective dependency derivations implicitly construct recoverable constituency-style ordered trees. For non-projective inputs, the interpretation can be used through pseudo-projective lifting and inverse decoding. A small implementation study confirms that the mapped derivations are executable in an existing neural transition-based parser.

Keywords

Cite

@article{arxiv.2603.27459,
  title  = {A tree interpretation of arc standard dependency derivation},
  author = {Zihao Huang and Ai Ka Lee and Jungyeul Park},
  journal= {arXiv preprint arXiv:2603.27459},
  year   = {2026}
}
R2 v1 2026-07-01T11:42:34.678Z