Search Results for author: Rik van Noord

Found 21 papers, 10 papers with code

MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages

no code implementations EAMT 2022 Marta Bañón, Miquel Esplà-Gomis, Mikel L. Forcada, Cristian García-Romero, Taja Kuzman, Nikola Ljubešić, Rik van Noord, Leopoldo Pla Sempere, Gema Ramírez-Sánchez, Peter Rupnik, Vít Suchomel, Antonio Toral, Tobias van der Werff, Jaume Zaragoza

We introduce the project “MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages”, funded by the Connecting Europe Facility, which is aimed at building monolingual and parallel corpora for under-resourced European languages.

Evaluating Text Generation from Discourse Representation Structures

1 code implementation ACL (GEM) 2021 Chunliu Wang, Rik van Noord, Arianna Bisazza, Johan Bos

We present an end-to-end neural approach to generate English sentences from formal meaning representations, Discourse Representation Structures (DRSs).

Text Generation

Transparent Semantic Parsing with Universal Dependencies Using Graph Transformations

1 code implementation COLING 2022 Wessel Poelman, Rik van Noord, Johan Bos

Even though many recent semantic parsers are based on deep learning methods, we should not forget that rule-based alternatives might offer advantages over neural approaches with respect to transparency, portability, and explainability.

Semantic Parsing

The Parallel Meaning Bank: A Framework for Semantically Annotating Multiple Languages

no code implementations29 Dec 2020 Lasha Abzianidze, Rik van Noord, Chunliu Wang, Johan Bos

This paper gives a general description of the ideas behind the Parallel Meaning Bank, a framework with the aim to provide an easy way to annotate compositional semantics for texts written in languages other than English.

Word Sense Disambiguation

Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT

2 code implementations EMNLP 2020 Rik van Noord, Antonio Toral, Johan Bos

We combine character-level and contextual language model representations to improve performance on Discourse Representation Structure parsing.

DRS Parsing Language Modelling

The First Shared Task on Discourse Representation Structure Parsing

no code implementations WS 2019 Lasha Abzianidze, Rik van Noord, Hessel Haagsma, Johan Bos

To measure similarity between two DRSs, they are represented in a clausal form, i. e. as a set of tuples.

DRS Parsing

Fair is Better than Sensational:Man is to Doctor as Woman is to Doctor

1 code implementation23 May 2019 Malvina Nissim, Rik van Noord, Rob van der Goot

However, beside the intrinsic problems with the analogy task as a bias detection tool, in this paper we show that a series of issues related to how analogies have been implemented and used might have yielded a distorted picture of bias in word embeddings.

Bias Detection Word Embeddings

Neural Boxer at the IWCS Shared Task on DRS Parsing

no code implementations WS 2019 Rik van Noord

This paper describes our participation in the shared task of Discourse Representation Structure parsing.

DRS Parsing

Exploring Neural Methods for Parsing Discourse Representation Structures

1 code implementation TACL 2018 Rik van Noord, Lasha Abzianidze, Antonio Toral, Johan Bos

Neural methods have had several recent successes in semantic parsing, though they have yet to face the challenge of producing meaning representations based on formal semantics.

DRS Parsing

Evaluating Scoped Meaning Representations

2 code implementations LREC 2018 Rik van Noord, Lasha Abzianidze, Hessel Haagsma, Johan Bos

A pilot study is performed to automatically find changes in meaning by comparing meaning representations of translations.

Natural Language Understanding Semantic Parsing

Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations

2 code implementations28 May 2017 Rik van Noord, Johan Bos

We evaluate the character-level translation method for neural semantic parsing on a large corpus of sentences annotated with Abstract Meaning Representations (AMRs).

AMR Parsing Translation

The Meaning Factory at SemEval-2017 Task 9: Producing AMRs with Neural Semantic Parsing

no code implementations SEMEVAL 2017 Rik van Noord, Johan Bos

We evaluate a semantic parser based on a character-based sequence-to-sequence model in the context of the SemEval-2017 shared task on semantic parsing for AMRs.

Data Augmentation POS +1

The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations

1 code implementation EACL 2017 Lasha Abzianidze, Johannes Bjerva, Kilian Evang, Hessel Haagsma, Rik van Noord, Pierre Ludmann, Duc-Duy Nguyen, Johan Bos

The Parallel Meaning Bank is a corpus of translations annotated with shared, formal meaning representations comprising over 11 million words divided over four languages (English, German, Italian, and Dutch).

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