The influence of fake news in the perception of reality has become a mainstream topic in the last years due to the fast propagation of misleading information.
Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies.
The vast majority of non-English corpora are derived from automatically filtered versions of CommonCrawl.
While interactions in social media such as Twitter occur in many natural languages, research on stance detection (the position or attitude expressed with respect to a specific topic) within the Natural Language Processing field has largely been done for English.
The TW-10 referendum Dataset released at IberEval 2018 is a previous effort to provide multilingual stance-annotated data in Catalan and Spanish.
The TW-10 Referendum Dataset released at IberEval 2018 is a previous effort to provide multilingual stance-annotated data in Catalan and Spanish.
This is suboptimal as, for many languages, the models have been trained on smaller (or lower quality) corpora.
This paper presents a new technique for creating monolingual and cross-lingual meta-embeddings.
In this paper we describe our participation to the Hyperpartisan News Detection shared task at SemEval 2019.
In this research note we present a language independent system to model Opinion Target Extraction (OTE) as a sequence labelling task.
This paper presents a simple, robust and (almost) unsupervised dictionary-based method, qwn-ppv (Q-WordNet as Personalized PageRanking Vector) to automatically generate polarity lexicons.
In this paper we present an approach to extract ordered timelines of events, their participants, locations and times from a set of multilingual and cross-lingual data sources.
Finally, the results show that our emphasis on clustering features is crucial to develop robust out-of-domain models.
Ranked #55 on Named Entity Recognition on CoNLL 2003 (English)
IXA pipeline is a modular set of Natural Language Processing tools (or pipes) which provide easy access to NLP technology.
In this paper we focus on the creation of general-purpose (as opposed to domain-specific) polarity lexicons in five languages: French, Italian, Dutch, English and Spanish using WordNet propagation.
Subtitling and audiovisual translation have been recognized as areas that could greatly benefit from the introduction of Statistical Machine Translation (SMT) followed by post-editing, in order to increase efficiency of subtitle production process.