Search Results for author: Diego Alves

Found 9 papers, 0 papers with code

Multilingual Comparative Analysis of Deep-Learning Dependency Parsing Results Using Parallel Corpora

no code implementations LREC (BUCC) 2022 Diego Alves, Marko Tadić, Božo Bekavac

This article presents a comparative analysis of dependency parsing results for a set of 16 languages, coming from a large variety of linguistic families and genera, whose parallel corpora were used to train a deep-learning tool.

Dependency Parsing Language Modelling

OEKG: The Open Event Knowledge Graph

no code implementations28 Feb 2023 Simon Gottschalk, Endri Kacupaj, Sara Abdollahi, Diego Alves, Gabriel Amaral, Elisavet Koutsiana, Tin Kuculo, Daniela Major, Caio Mello, Gullal S. Cheema, Abdul Sittar, Swati, Golsa Tahmasebzadeh, Gaurish Thakkar

Accessing and understanding contemporary and historical events of global impact such as the US elections and the Olympic Games is a major prerequisite for cross-lingual event analytics that investigate event causes, perception and consequences across country borders.

Image Retrieval Knowledge Graphs +5

Building and Evaluating Universal Named-Entity Recognition English corpus

no code implementations14 Dec 2022 Diego Alves, Gaurish Thakkar, Marko Tadić

This article presents the application of the Universal Named Entity framework to generate automatically annotated corpora.

named-entity-recognition Named Entity Recognition +1

Natural Language Processing Chains Inside a Cross-lingual Event-Centric Knowledge Pipeline for European Union Under-resourced Languages

no code implementations LREC 2020 Diego Alves, Gaurish Thakkar, Marko Tadić

Due to the differences in terms of availability of language resources for each language, we have built this strategy in three steps, starting with processing chains for the well-resourced languages and finishing with the development of new modules for the under-resourced ones.

named-entity-recognition Named Entity Recognition +1

Evaluating Language Tools for Fifteen EU-official Under-resourced Languages

no code implementations LREC 2020 Diego Alves, Gaurish Thakkar, Marko Tadić

We considered the difference between reported and our tested results within a single percentage point as being within the limits of acceptable tolerance and thus consider this result as reproducible.

UNER: Universal Named-Entity RecognitionFramework

no code implementations23 Oct 2020 Diego Alves, Tin Kuculo, Gabriel Amaral, Gaurish Thakkar, Marko Tadic

We introduce the Universal Named-Entity Recognition (UNER)framework, a 4-level classification hierarchy, and the methodology that isbeing adopted to create the first multilingual UNER corpus: the SETimesparallel corpus annotated for named-entities.

Knowledge Graphs named-entity-recognition +2

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