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Recent efforts to consolidate guidelines and treebanks in the Universal Dependencies project raise the expectation that joint training and dataset comparison is increasingly possible for high-resource languages such as English, which have…

Computation and Language · Computer Science 2023-02-02 Amir Zeldes , Nathan Schneider

The paper proposes annotation guidelines for syntactic dependencies that span across speaker turns - including collaborative coconstructions proper, wh-question answers, and backchannels - in spoken language treebanks within the Universal…

Computation and Language · Computer Science 2026-03-31 Ludovica Pannitto , Sylvain Kahane , Kaja Dobrovoljc , Elena Battaglia , Bruno Guillaume , Caterina Mauri , Eleonora Zucchini

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full story. Grammatical constructions that convey meaning…

Universal Dependencies (UD), while widely regarded as the most successful linguistic framework for cross-lingual syntactic representation, remains underexplored in terms of its effectiveness. This paper addresses this gap by integrating UD…

Computation and Language · Computer Science 2025-06-06 Wenxi Li

Syntactic dependencies can be predicted with high accuracy, and are useful for both machine-learned and pattern-based information extraction tasks. However, their utility can be improved. These syntactic dependencies are designed to…

Computation and Language · Computer Science 2020-06-05 Aryeh Tiktinsky , Yoav Goldberg , Reut Tsarfaty

This work focuses on analyzing the form and extent of syntactic abstraction captured by BERT by extracting labeled dependency trees from self-attentions. Previous work showed that individual BERT heads tend to encode particular dependency…

Computation and Language · Computer Science 2021-01-01 Tomasz Limisiewicz , Rudolf Rosa , David Mareček

Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework. The annotation consists in a linguistically motivated word…

We describe a cross-lingual adaptation method based on syntactic parse trees obtained from the Universal Dependencies (UD), which are consistent across languages, to develop classifiers in low-resource languages. The idea of UD parsing is…

Computation and Language · Computer Science 2020-03-31 Nasrin Taghizadeh , Heshaam Faili

We describe and evaluate different approaches to the conversion of gold standard corpus data from Stanford Typed Dependencies (SD) and Penn-style constituent trees to the latest English Universal Dependencies representation (UD 2.2). Our…

Computation and Language · Computer Science 2019-09-04 Siyao Peng , Amir Zeldes

Universal Dependencies (UD) offer a uniform cross-lingual syntactic representation, with the aim of advancing multilingual applications. Recent work shows that semantic parsing can be accomplished by transforming syntactic dependencies to…

Computation and Language · Computer Science 2017-08-30 Siva Reddy , Oscar Täckström , Slav Petrov , Mark Steedman , Mirella Lapata

Treebank translation is a promising method for cross-lingual transfer of syntactic dependency knowledge. The basic idea is to map dependency arcs from a source treebank to its target translation according to word alignments. This method,…

Computation and Language · Computer Science 2019-09-06 Zhang Meishan , Zhang Yue , Fu Guohong

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…

Computation and Language · Computer Science 2026-05-28 Zihao Huang , Ai Ka Lee , Jungyeul Park

We propose a transition-based bubble parser to perform coordination structure identification and dependency-based syntactic analysis simultaneously. Bubble representations were proposed in the formal linguistics literature decades ago; they…

Computation and Language · Computer Science 2021-07-16 Tianze Shi , Lillian Lee

Languages may encode similar meanings using different sentence structures. This makes it a challenge to provide a single set of formal rules that can derive meanings from sentences in many languages at once. To overcome the challenge, we…

Computation and Language · Computer Science 2024-03-05 Laurestine Bradford , Timothy John O'Donnell , Siva Reddy

We use reinforcement learning to learn tree-structured neural networks for computing representations of natural language sentences. In contrast with prior work on tree-structured models in which the trees are either provided as input or…

Computation and Language · Computer Science 2016-11-29 Dani Yogatama , Phil Blunsom , Chris Dyer , Edward Grefenstette , Wang Ling

Low-resource machine translation requires methods that differ from those used for high-resource languages. This paper proposes a novel in-context learning approach to support low-resource machine translation of the Coptic language to…

Computation and Language · Computer Science 2026-05-28 Abhishek Purushothama , Emma Thronson , Alexia Guo , Amir Zeldes

We explore the link between the extent to which syntactic relations are preserved in translation and the ease of correctly constructing a parse tree in a zero-shot setting. While previous work suggests such a relation, it tends to focus on…

Computation and Language · Computer Science 2021-10-12 Ofir Arviv , Dmitry Nikolaev , Taelin Karidi , Omri Abend

We compare the performance of a transition-based parser in regards to different annotation schemes. We pro-pose to convert some specific syntactic constructions observed in the universal dependency treebanks into a so-called more standard…

Computation and Language · Computer Science 2025-03-11 Guillaume Wisniewski , Ophélie Lacroix

In this paper, we first open on important issues regarding the Penn Korean Universal Treebank (PKT-UD) and address these issues by revising the entire corpus manually with the aim of producing cleaner UD annotations that are more faithful…

Computation and Language · Computer Science 2020-05-27 Tae Hwan Oh , Ji Yoon Han , Hyonsu Choe , Seokwon Park , Han He , Jinho D. Choi , Na-Rae Han , Jena D. Hwang , Hansaem Kim

AM dependency parsing is a method for neural semantic graph parsing that exploits the principle of compositionality. While AM dependency parsers have been shown to be fast and accurate across several graphbanks, they require explicit…

Computation and Language · Computer Science 2021-06-09 Jonas Groschwitz , Meaghan Fowlie , Alexander Koller
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