Euskarako ezagutza-base lexiko-semantikoaren eredu-hautaketa eta garapena: EuskalWordNet

Natural Language Processing techniques need to develop lexical-semantic knowledge bases (LSKB) in order to perform semantic interpretation. The IXA group decided to develop a Basque LSKB called EuskalWordNet for this reason. EuskalWordNet is based on WordNet and its multilingual counterparts EuroWordNet and the Multilingual Central Repository (MCR). This paper reviews the theoretical and practical aspects of the EuskalWordNet LSKB, as well as the steps followed in its construction

Euskarako ezagutza-base lexiko-semantikoaren eredu-hautaketa eta garapena: EuskalWordNet

Natural Language Processing techniques need to develop lexical-semantic knowledge bases (LSKB) in order to perform semantic interpretation. The IXA group decided to develop a Basque LSKB called EuskalWordNet for this reason. EuskalWordNet is based on WordNet and its multilingual counterparts EuroWordNet and the Multilingual Central Repository (MCR). This paper reviews the theoretical and practical aspects of the EuskalWordNet LSKB, as well as the steps followed in its construction

An Approach for Automatic Generation of on-line Information Systems based on the Integration of Natural Language Processing and Adaptive Hypermedia Techniques

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Politécnica Superior, Departamento de ingeniería informática. Fecha de lectura: 29-05-200

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Tune your brown clustering, please

Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly unexplored. Accordingly, we present information for practitioners on the behaviour of Brown clustering in order to assist hyper-parametre tuning, in the form of a theoretical model of Brown clustering utility. This model is then evaluated empirically in two sequence labelling tasks over two text types. We explore the dynamic between the input corpus size, chosen number of classes, and quality of the resulting clusters, which has an impact for any approach using Brown clustering. In every scenario that we examine, our results reveal that the values most commonly used for the clustering are sub-optimal

Multiword expressions at length and in depth

The annual workshop on multiword expressions takes place since 2001 in conjunction with major computational linguistics conferences and attracts the attention of an ever-growing community working on a variety of languages, linguistic phenomena and related computational processing issues. MWE 2017 took place in Valencia, Spain, and represented a vibrant panorama of the current research landscape on the computational treatment of multiword expressions, featuring many high-quality submissions. Furthermore, MWE 2017 included the first shared task on multilingual identification of verbal multiword expressions. The shared task, with extended communal work, has developed important multilingual resources and mobilised several research groups in computational linguistics worldwide. This book contains extended versions of selected papers from the workshop. Authors worked hard to include detailed explanations, broader and deeper analyses, and new exciting results, which were thoroughly reviewed by an internationally renowned committee. We hope that this distinctly joint effort will provide a meaningful and useful snapshot of the multilingual state of the art in multiword expressions modelling and processing, and will be a point point of reference for future work

A pilot study of English selectional preferences and their cross-lingual compatibility with Basque

The specific goals of this experiment are to study automatically acquired English selectional preferences from a number of sources, and to assess portability and compatibility issues with regard to selectional preferences acquired for Basque. We decided to study a wide-range of techniques and issues, with the aim of providing an analysis of the interplay of selectional-learning techniques, domain and multilinguality

Extended papers from the MWE 2017 workshop

The annual workshop on multiword expressions takes place since 2001 in conjunction with major computational linguistics conferences and attracts the attention of an ever-growing community working on a variety of languages, linguistic phenomena and related computational processing issues. MWE 2017 took place in Valencia, Spain, and represented a vibrant panorama of the current research landscape on the computational treatment of multiword expressions, featuring many high-quality submissions. Furthermore, MWE 2017 included the first shared task on multilingual identification of verbal multiword expressions. The shared task, with extended communal work, has developed important multilingual resources and mobilised several research groups in computational linguistics worldwide. This book contains extended versions of selected papers from the workshop. Authors worked hard to include detailed explanations, broader and deeper analyses, and new exciting results, which were thoroughly reviewed by an internationally renowned committee. We hope that this distinctly joint effort will provide a meaningful and useful snapshot of the multilingual state of the art in multiword expressions modelling and processing, and will be a point point of reference for future work