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JRC TMA-CC: Slavic Named Entity Recognition and Linking. Participation in the BSNLP-2019 shared task
We report on the participation of the JRC Text Mining and Analysis Competence Centre (TMA-CC) in the BSNLP-2019 Shared Task, which focuses on named-entity recognition, lemmatisation and cross-lingual linking.
Large-scale news entity sentiment analysis
We work on detecting positive or negative sentiment towards named entities in very large volumes of news articles.
Multi-word Entity Classification in a Highly Multilingual Environment
This paper describes an approach for the classification of millions of existing multi-word entities (MWEntities), such as organisation or event names, into thirteen category types, based only on the tokens they contain.
Cross-lingual Linking of Multi-word Entities and their corresponding Acronyms
This paper reports on an approach and experiments to automatically build a cross-lingual multi-word entity resource.
Observing Trends in Automated Multilingual Media Analysis
Any large organisation, be it public or private, monitors the media for information to keep abreast of developments in their field of interest, and usually also to become aware of positive or negative opinions expressed towards them.
Experiments to Improve Named Entity Recognition on Turkish Tweets
In these experiments, starting with a baseline named entity recognition system, we adapt its recognition rules and resources to better fit Twitter language by relaxing its capitalization constraint and by diacritics-based expansion of its lexical resources, and we employ a simplistic normalization scheme on tweets to observe the effects of these on the overall named entity recognition performance on Turkish tweets.
Named Entity Recognition on Turkish Tweets
Various recent studies show that the performance of named entity recognition (NER) systems developed for well-formed text types drops significantly when applied to tweets.
DCEP -Digital Corpus of the European Parliament
We are presenting a new highly multilingual document-aligned parallel corpus called DCEP - Digital Corpus of the European Parliament.
Resource Creation and Evaluation for Multilingual Sentiment Analysis in Social Media Texts
We show that the use of machine translated data obtained similar results as the use of native-speaker translations of the same data.
Clustering of Multi-Word Named Entity variants: Multilingual Evaluation
Multi-word entities, such as organisation names, are frequently written in many different ways.
Media monitoring and information extraction for the highly inflected agglutinative language Hungarian
In this paper, we describe the effort of adding to EMM Hungarian text mining tools for news gathering; document categorisation; named entity recognition and classification for persons, organisations and locations; name lemmatisation; quotation recognition; and cross-lingual linking of related news clusters.
A survey of methods to ease the development of highly multilingual text mining applications
While Information Extraction and other text mining software can, in principle, be developed for many languages, most text analysis tools have only been applied to small sets of languages because the development effort per language is large.
ONTS: "Optima" News Translation System
We propose a real-time machine translation system that allows users to select a news category and to translate the related live news articles from Arabic, Czech, Danish, Farsi, French, German, Italian, Polish, Portuguese, Spanish and Turkish into English.
Sentiment Analysis in the News
We identified three subtasks that need to be addressed: definition of the target; separation of the good and bad news content from the good and bad sentiment expressed on the target; and analysis of clearly marked opinion that is expressed explicitly, not needing interpretation or the use of world knowledge.
Acronym recognition and processing in 22 languages
We are presenting work on recognising acronyms of the form Long-Form (Short-Form) such as "International Monetary Fund (IMF)" in millions of news articles in twenty-two languages, as part of our more general effort to recognise entities and their variants in news text and to use them for the automatic analysis of the news, including the linking of related news across languages.
JRC-Names: A freely available, highly multilingual named entity resource
This paper describes a new, freely available, highly multilingual named entity resource for person and organisation names that has been compiled over seven years of large-scale multilingual news analysis combined with Wikipedia mining, resulting in 205, 000 per-son and organisation names plus about the same number of spelling variants written in over 20 different scripts and in many more languages.
An introduction to the Europe Media Monitor family of applications
In the European Union with its 23 official languages, it is particularly important to cover media reports in many languages in order to capture the complementary news content published in the different countries.
JRC EuroVoc Indexer JEX - A freely available multi-label categorisation tool
EuroVoc (2012) is a highly multilingual thesaurus consisting of over 6, 700 hierarchically organised subject domains used by European Institutions and many authorities in Member States of the European Union (EU) for the classification and retrieval of official documents.
DGT-TM: A freely Available Translation Memory in 22 Languages
The European Commission's (EC) Directorate General for Translation, together with the EC's Joint Research Centre, is making available a large translation memory (TM; i. e. sentences and their professionally produced translations) covering twenty-two official European Union (EU) languages and their 231 language pairs.
