Search Results for author: Jakub Waszczuk

Found 14 papers, 3 papers with code

Polish corpus of verbal multiword expressions

1 code implementation COLING (MWE) 2020 Agata Savary, Jakub Waszczuk

This paper describes a manually annotated corpus of verbal multi-word expressions in Polish.

Improving Low-resource RRG Parsing with Cross-lingual Self-training

no code implementations COLING 2022 Kilian Evang, Laura Kallmeyer, Jakub Waszczuk, Kilu von Prince, Tatiana Bladier, Simon Petitjean

Starting from an existing RRG parser, we propose two strategies for low-resource parsing: first, we extend the parsing model into a cross-lingual parser, exploiting the parallel data in the high-resource language and unsupervised word alignments by providing internal states of the source-language parser to the target-language parser.

Constituency Parsing

Statistical Parsing of Tree Wrapping Grammars

1 code implementation COLING 2020 Tatiana Bladier, Jakub Waszczuk, Laura Kallmeyer

We describe an approach to statistical parsing with Tree-Wrapping Grammars (TWG).

Supervised Disambiguation of German Verbal Idioms with a BiLSTM Architecture

no code implementations WS 2020 Rafael Ehren, Timm Lichte, Laura Kallmeyer, Jakub Waszczuk

Supervised disambiguation of verbal idioms (VID) poses special demands on the quality and quantity of the annotated data used for learning and evaluation.

Contemplata, a Free Platform for Constituency Treebank Annotation

no code implementations LREC 2020 Jakub Waszczuk, Ilaine Wang, Jean-Yves Antoine, Ana{\"\i}s Halftermeyer

This paper describes Contemplata, an annotation platform that offers a generic solution for treebank building as well as treebank enrichment with relations between syntactic nodes.

A Neural Graph-based Approach to Verbal MWE Identification

1 code implementation WS 2019 Jakub Waszczuk, Rafael Ehren, Regina Stodden, Laura Kallmeyer

We propose to tackle the problem of verbal multiword expression (VMWE) identification using a neural graph parsing-based approach.

TRAVERSAL at PARSEME Shared Task 2018: Identification of Verbal Multiword Expressions Using a Discriminative Tree-Structured Model

no code implementations COLING 2018 Jakub Waszczuk

This paper describes a system submitted to the closed track of the PARSEME shared task (edition 1. 1) on automatic identification of verbal multiword expressions (VMWEs).

regression

Projecting Multiword Expression Resources on a Polish Treebank

no code implementations WS 2017 Agata Savary, Jakub Waszczuk

Multiword expressions (MWEs) are linguistic objects containing two or more words and showing idiosyncratic behavior at different levels.

Promoting multiword expressions in A* TAG parsing

no code implementations COLING 2016 Jakub Waszczuk, Agata Savary, Yannick Parmentier

Multiword expressions (MWEs) are pervasive in natural languages and often have both idiomatic and compositional readings, which leads to high syntactic ambiguity.

TAG

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