Multi3Generation: Multitask, Multilingual, Multimodal Language Generation

no code implementations • EAMT 2022 • Anabela Barreiro, José GC de Souza, Albert Gatt, Mehul Bhatt, Elena Lloret, Aykut Erdem, Dimitra Gkatzia, Helena Moniz, Irene Russo, Fabio Kepler, Iacer Calixto, Marcin Paprzycki, François Portet, Isabelle Augenstein, Mirela Alhasani

This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generation (CA18231), an interdisciplinary network of research groups working on different aspects of language generation.

Text Generation

Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning

no code implementations • LREC 2020 • Lionel Nicolas, Verena Lyding, Claudia Borg, Corina Forascu, Kar{\"e}n Fort, Katerina Zdravkova, Iztok Kosem, Jaka {\v{C}}ibej, {\v{S}}pela Arhar Holdt, Alice Millour, Alex K{\"o}nig, er, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Anisia Katinskaia, Anabela Barreiro, Lavinia Aparaschivei, Yaakov HaCohen-Kerner

We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved.

Paraphrastic Variance between European and Brazilian Portuguese

no code implementations • COLING 2018 • Anabela Barreiro, Cristina Mota

This paper presents a methodology to extract a paraphrase database for the European and Brazilian varieties of Portuguese, and discusses a set of paraphrastic categories of multiwords and phrasal units, such as the compounds {``}toda a gente{''} versus {``}todo o mundo{''} {`}everybody{'} or the gerundive constructions [estar a + V-Inf] versus [ficar + V-Ger] (e. g., {``}estive a observar{''} | {``}fiquei observando{''} {`}I was observing{'}), which are extremely relevant to high quality paraphrasing.

Machine Translation Question Answering +2

Contractions: To Align or Not to Align, That Is the Question

no code implementations • COLING 2018 • Anabela Barreiro, Fern Batista, o

On the other hand, contractions tend to be maintained when they occur in the beginning or in the middle of the multiword unit, i. e., in the frozen part of the multiword (e. g., [no que diz respeito a] | [with regard to] or [al{\'e}m disso] [in addition].

Machine Translation Translation

Machine Translation of Non-Contiguous Multiword Units

no code implementations • WS 2016 • Anabela Barreiro, Fern Batista, o

Machine Translation Translation

Port4NooJ v3.0: Integrated Linguistic Resources for Portuguese NLP

no code implementations • LREC 2016 • Cristina Mota, Paula Carvalho, Anabela Barreiro

The Port4NooJ v3. 0 resource is innovative in terms of the specificity of the linguistic knowledge it incorporates.

named-entity-recognition Named Entity Recognition +4

Linguistic Evaluation of Support Verb Constructions by OpenLogos and Google Translate

no code implementations • LREC 2014 • Anabela Barreiro, Johanna Monti, Brigitte Orliac, Susanne Preu{\ss}, Kutz Arrieta, Wang Ling, Fern Batista, o, Isabel Trancoso

This paper presents a systematic human evaluation of translations of English support verb constructions produced by a rule-based machine translation (RBMT) system (OpenLogos) and a statistical machine translation (SMT) system (Google Translate) for five languages: French, German, Italian, Portuguese and Spanish.

Machine Translation Translation

OpenLogos Semantico-Syntactic Knowledge-Rich Bilingual Dictionaries

no code implementations • LREC 2014 • Anabela Barreiro, Fern Batista, o, Ricardo Ribeiro, Helena Moniz, Isabel Trancoso

This paper presents 3 sets of OpenLogos resources, namely the English-German, the English-French, and the English-Italian bilingual dictionaries.

Machine Translation Translation