Carla Parra Escartín

Also published as: Carla Parra Escartin, Carla Parra Escartín, Carla Parra


2020

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Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
André Martins | Helena Moniz | Sara Fumega | Bruno Martins | Fernando Batista | Luisa Coheur | Carla Parra | Isabel Trancoso | Marco Turchi | Arianna Bisazza | Joss Moorkens | Ana Guerberof | Mary Nurminen | Lena Marg | Mikel L. Forcada
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

2019

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Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)
Agata Savary | Carla Parra Escartín | Francis Bond | Jelena Mitrović | Verginica Barbu Mititelu
Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)

2018

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Edition 1.1 of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions
Carlos Ramisch | Silvio Ricardo Cordeiro | Agata Savary | Veronika Vincze | Verginica Barbu Mititelu | Archna Bhatia | Maja Buljan | Marie Candito | Polona Gantar | Voula Giouli | Tunga Güngör | Abdelati Hawwari | Uxoa Iñurrieta | Jolanta Kovalevskaitė | Simon Krek | Timm Lichte | Chaya Liebeskind | Johanna Monti | Carla Parra Escartín | Behrang QasemiZadeh | Renata Ramisch | Nathan Schneider | Ivelina Stoyanova | Ashwini Vaidya | Abigail Walsh
Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)

This paper describes the PARSEME Shared Task 1.1 on automatic identification of verbal multiword expressions. We present the annotation methodology, focusing on changes from last year’s shared task. Novel aspects include enhanced annotation guidelines, additional annotated data for most languages, corpora for some new languages, and new evaluation settings. Corpora were created for 20 languages, which are also briefly discussed. We report organizational principles behind the shared task and the evaluation metrics employed for ranking. The 17 participating systems, their methods and obtained results are also presented and analysed.

2017

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Improving Evaluation of Document-level Machine Translation Quality Estimation
Yvette Graham | Qingsong Ma | Timothy Baldwin | Qun Liu | Carla Parra | Carolina Scarton
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

Meaningful conclusions about the relative performance of NLP systems are only possible if the gold standard employed in a given evaluation is both valid and reliable. In this paper, we explore the validity of human annotations currently employed in the evaluation of document-level quality estimation for machine translation (MT). We demonstrate the degree to which MT system rankings are dependent on weights employed in the construction of the gold standard, before proposing direct human assessment as a valid alternative. Experiments show direct assessment (DA) scores for documents to be highly reliable, achieving a correlation of above 0.9 in a self-replication experiment, in addition to a substantial estimated cost reduction through quality controlled crowd-sourcing. The original gold standard based on post-edits incurs a 10–20 times greater cost than DA.

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Ethical Considerations in NLP Shared Tasks
Carla Parra Escartín | Wessel Reijers | Teresa Lynn | Joss Moorkens | Andy Way | Chao-Hong Liu
Proceedings of the First ACL Workshop on Ethics in Natural Language Processing

Shared tasks are increasingly common in our field, and new challenges are suggested at almost every conference and workshop. However, as this has become an established way of pushing research forward, it is important to discuss how we researchers organise and participate in shared tasks, and make that information available to the community to allow further research improvements. In this paper, we present a number of ethical issues along with other areas of concern that are related to the competitive nature of shared tasks. As such issues could potentially impact on research ethics in the Natural Language Processing community, we also propose the development of a framework for the organisation of and participation in shared tasks that can help mitigate against these issues arising.

2016

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PARSEME Survey on MWE Resources
Gyri Smørdal Losnegaard | Federico Sangati | Carla Parra Escartín | Agata Savary | Sascha Bargmann | Johanna Monti
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper summarizes the preliminary results of an ongoing survey on multiword resources carried out within the IC1207 Cost Action PARSEME (PARSing and Multi-word Expressions). Despite the availability of language resource catalogs and the inventory of multiword datasets on the SIGLEX-MWE website, multiword resources are scattered and difficult to find. In many cases, language resources such as corpora, treebanks, or lexical databases include multiwords as part of their data or take them into account in their annotations. However, these resources need to be centralized to make them accessible. The aim of this survey is to create a portal where researchers can easily find multiword(-aware) language resources for their research. We report on the design of the survey and analyze the data gathered so far. We also discuss the problems we have detected upon examination of the data as well as possible ways of enhancing the survey.

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Combining Translation Memories and Syntax-Based SMT: Experiments with Real Industrial Data
Liangyou Li | Carla Parra Escartin | Qun Liu
Proceedings of the 19th Annual Conference of the European Association for Machine Translation

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Semantic Textual Similarity in Quality Estimation
Hanna Bechara | Carla Parra Escartin | Constantin Orasan | Lucia Specia
Proceedings of the 19th Annual Conference of the European Association for Machine Translation

2015

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A fuzzier approach to machine translation evaluation: A pilot study on post-editing productivity and automated metrics in commercial settings
Carla Parra Escartín | Manuel Arcedillo
Proceedings of the Fourth Workshop on Hybrid Approaches to Translation (HyTra)

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Creation of new TM segments: Fulfilling translators’ wishes
Carla Parra Escartín
Proceedings of the Workshop Natural Language Processing for Translation Memories

2014

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German Compounds and Statistical Machine Translation. Can they get along?
Carla Parra Escartín | Stephan Peitz | Hermann Ney
Proceedings of the 10th Workshop on Multiword Expressions (MWE)

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Chasing the Perfect Splitter: A Comparison of Different Compound Splitting Tools
Carla Parra Escartín
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper reports on the evaluation of two compound splitters for German. Compounding is a very frequent phenomenon in German and thus efficient ways of detecting and correctly splitting compound words are needed for natural language processing applications. This paper presents different strategies for compound splitting, focusing on German. Four compound splitters for German are presented. Two of them were used in Statistical Machine Translation (SMT) experiments, obtaining very similar qualitative scores in terms of BLEU and TER and therefore a thorough evaluation of both has been carried out.

2012

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Design and compilation of a specialized Spanish-German parallel corpus
Carla Parra Escartín
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper discusses the design and compilation of the TRIS corpus, a specialized parallel corpus of Spanish and German texts. It will be used for phraseological research aimed at improving statistical machine translation. The corpus is based on the European database of Technical Regulations Information System (TRIS), containing 995 original documents written in German and Spanish and their translations into Spanish and German respectively. This parallel corpus is under development and the first version with 97 aligned file pairs was released in the first META-NORD upload of metadata and resources in November 2011. The second version of the corpus, described in the current paper, contains 205 file pairs which have been completely aligned at sentence level, which account for approximately 1,563,000 words and 70,648 aligned sentence pairs.