Papers with syntactic parser

7 papers
Unsupervised Natural Language Parsing (Introductory Tutorial) (2021.eacl-tutorials)

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Challenge: Unsupervised parsing learns a syntactic parser from training sentences without parse tree annotations.
Approach: This tutorial will introduce what unsupervised parsing does and how it can be useful for and beyond syntactic parse.
Outcome: This paper will provide an overview of major approaches to unsupervised parsing and analyze their strengths and weaknesses.
A Unified RvNN Framework for End-to-End Chinese Discourse Parsing (C18-2)

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Challenge: Existing work on Chinese discourse parser relies on external packages to extract linguistic features from free text.
Approach: They propose an end-to-end Chinese discourse parser based on recursive neural network to jointly model the subtasks including elementary discourse unit segmentation, tree structure construction, center labeling, and sense labeling.
Outcome: The proposed framework achieves state-of-the-art in the Chinese Discourse Treebank dataset.
Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech (2024.acl-short)

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Challenge: Direct dependency parsing of the speech signal is proposed as a way of incorporating prosodic information into the parser and bypassing the limitations of a pipeline approach.
Approach: They propose to use graph-based parsing and sequence labeling based parses to integrate prosodic information into the parser and bypass limitations of pipeline approaches.
Outcome: The proposed graph based approach outperforms a pipeline approach on a large treebank of spoken french, despite having 30% fewer parameters.
Phrase-level Textual Adversarial Attack with Label Preservation (2022.findings-naacl)

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Challenge: Existing adversarial attacks are usually realized through word-level or sentence-level perturbations, which either limit the perturbation space or sacrifice fluency and textual quality.
Approach: They propose a phrase-level perturbation-based adversarial ATtack that generates adversarials through phrase- level perturbations.
Outcome: The proposed approach improves the performance of natural language processing models by reducing the need for word-level perturbations and preserving the fluency and grammaticality of the samples.
Semantic Role Labeling with Heterogeneous Syntactic Knowledge (2020.coling-main)

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Challenge: Recent work on incorporating syntactic knowledge into neural semantic role labeling has gained much attention . incorporating heterogeneous syntaktic knowledge brings significant improvements over strong baselines .
Approach: They propose to encode heterogeneous syntactic knowledge for SRL from explicit and implicit representations from heterogenous treebanks.
Outcome: The proposed approaches improve on two widely-used benchmark datasets.
A Framenet and Frame Annotator for German Social Media (2022.lrec-1)

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Challenge: In corpus linguistics, semantic annotation is a valuable addition to ordinary, morphosyntactic tagging, lemmatization and dependency relations.
Approach: They propose a parsing- and annotation-oriented framenet for German with almost 15,000 frames . they propose valency, syntactic function and semantic noun class as input conditions for frame disambiguation .
Outcome: The proposed resource is based on a Danish/German study on hate speech . it achieves an overall F-score for frame senses of 93.6% on twitter .
Towards Universal Dependencies for Ancash Quechua (2024.lrec-main)

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Challenge: a new corpus of Quechua morphosyntactic features are described for Ancash Quechuan, the majority variety of the Central Quechual language family . the morphology of the language is a feature of the universal dependency (UD) schema . a syntactical parser would be the first NLP tool for a Quechuang language of this family based on the UD schema based upon the typology of the languages .
Approach: They propose to describe some morphosyntactic features of Ancash Quechua . they propose to build a corpus annotated according to the universal dependency schema .
Outcome: The proposed corpus is the first bilingual and sentence-aligned digital corpus in Ancash Quechua and Spanish.

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