Papers by Monica Monachini

4 papers
Language Technologies for the Creation of Multilingual Terminologies. Lessons Learned from the SSHOC Project (2022.lrec-1)

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Challenge: Language Technologies can help in promoting and facilitating multilingualism in the Social Sciences and Humanities domain.
Approach: They propose to use Natural Language Processing and Machine Translation to provide tools to foster multilingual access and discovery to SSH content across different languages.
Outcome: The proposed tools prove to be a valid asset to translation tasks . validation of results by domain experts proficient in the language is an unavoidable phase of the whole workflow.
The LREC Workshops Map (L18-1)

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Challenge: a corpus of workshops titles and related presentations has been retrieved from the conference's website . data is used to analyze the research presented at the conferences over the years 1998-2016 .
Approach: a paper aims to present an overview of the research presented at the LREC workshops over the years 1998-2016.
Outcome: The aim of the present study is to shed light on the community represented by workshop participants over the years 1998-2016.
A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment (2020.lrec-1)

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Challenge: a new dataset aims to align monolingual dictionaries with a single sense level for 15 languages . this dataset covers a wide range of languages and resources .
Approach: They propose to manually align monolingual dictionaries with possible semantic relationships . they use 15 languages to create a new baseline for the task of monolingual word sense alignment .
Outcome: The proposed dataset covers 15 languages and covers the more challenging task of linking general-purpose language.
One Language to rule them all: modelling Morphological Patterns in a Large Scale Italian Lexicon with SWRL (L18-1)

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Challenge: Linked data (LD) is a popular way of publishing lexical resources, but technical limitations and potentialities of LD are not understood as they should be.
Approach: They propose to use the Semantic Web Rule Language to encode morphological patterns for a lexicographic publication as linked open data.
Outcome: The proposed language allows the automatic derivation of inflectional variants of entries in the lexicon.

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