Search Results for author: Maria Mitrofan

Found 22 papers, 1 papers with code

Leaving No Stone Unturned When Identifying and Classifying Verbal Multiword Expressions in the Romanian Wordnet

no code implementations GWC 2019 Verginica Mititelu, Maria Mitrofan

Given the alignment of the Romanian wordnet to the Princeton WordNet, this type of annotation can be further used for drawing comparisons between equivalent verbal literals in various languages, provided that such information is annotated in the wordnets of the respective languages and their wordnets are aligned to Princeton WordNet, and thus to the Romanian wordnet.

Evaluating the Wordnet and CoRoLa-based Word Embedding Vectors for Romanian as Resources in the Task of Microworlds Lexicon Expansion

no code implementations GWC 2019 Elena Irimia, Maria Mitrofan, Verginica Mititelu

The evaluation is made for two situations: one in which the words are not semantically disambiguated before expanding the lexicon, and another one in which they are disambiguated with senses from the Romanian wordnet.

A Romanian Treebank Annotated with Verbal Multiword Expressions

no code implementations CLIB 2022 Verginica Barbu Mititelu, Mihaela Cristescu, Maria Mitrofan, Bianca-Mădălina Zgreabăn, Elena-Andreea Bărbulescu

In this paper we present a new version of the Romanian journalistic treebank annotated with verbal multiword expressions of four types: idioms, light verb constructions, reflexive verbs and inherently adpositional verbs, the last type being recently added to the corpus.

Romanian Language Translation in the RELATE Platform

no code implementations loresmt (COLING) 2022 Vasile Pais, Maria Mitrofan, Andrei-Marius Avram

This paper presents the usage of the RELATE platform for translation tasks involving the Romanian language.

Translation

RACAI@SMM4H’22: Tweets Disease Mention Detection Using a Neural Lateral Inhibitory Mechanism

no code implementations SMM4H (COLING) 2022 Andrei-Marius Avram, Vasile Pais, Maria Mitrofan

This paper presents our system employed for the Social Media Mining for Health (SMM4H) 2022 competition Task 10 - SocialDisNER.

Improving Romanian BioNER Using a Biologically Inspired System

no code implementations BioNLP (ACL) 2022 Maria Mitrofan, Vasile Pais

Recognition of named entities present in text is an important step towards information extraction and natural language understanding.

named-entity-recognition Named Entity Recognition +2

Challenges in Creating a Representative Corpus of Romanian Micro-Blogging Text

no code implementations CMLC (LREC) 2022 Vasile Pais, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Roxana Micu, Carol Luca Gasan

Following the successful creation of a national representative corpus of contemporary Romanian language, we turned our attention to the social media text, as present in micro-blogging platforms.

Use Case: Romanian Language Resources in the LOD Paradigm

no code implementations LDL (ACL) 2022 Verginica Barbu Mititelu, Elena Irimia, Vasile Pais, Andrei-Marius Avram, Maria Mitrofan

In this paper, we report on (i) the conversion of Romanian language resources to the Linked Open Data specifications and requirements, on (ii) their publication and (iii) interlinking with other language resources (for Romanian or for other languages).

Word Embeddings

An Open-Domain QA System for e-Governance

no code implementations CLIB 2022 Radu Ion, Andrei-Marius Avram, Vasile Păiş, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Valentin Badea

The paper will present the QA system and its integration with the Romanian language technologies portal RELATE, the COVID-19 data set and different evaluations of the QA performance.

Open-Domain Question Answering

Human-Machine Interaction Speech Corpus from the ROBIN project

no code implementations22 Nov 2021 Vasile Păiş, Radu Ion, Andrei-Marius Avram, Elena Irimia, Verginica Barbu Mititelu, Maria Mitrofan

The paper contains a detailed description of the acquisition process, corpus statistics as well as an evaluation of the corpus influence on a low-latency ASR system as well as a dialogue component.

Collection and Annotation of the Romanian Legal Corpus

no code implementations LREC 2020 Dan Tufi{\textcommabelow{s}}, Maria Mitrofan, Vasile P{\u{a}}i{\textcommabelow{s}}, Radu Ion, Andrei Coman

We present the Romanian legislative corpus which is a valuable linguistic asset for the development of machine translation systems, especially for under-resourced languages.

Machine Translation POS +1

RACAI's System at PharmaCoNER 2019

no code implementations WS 2019 Radu Ion, Vasile Florian P{\u{a}}i{\textcommabelow{s}}, Maria Mitrofan

This paper describes the Named Entity Recognition system of the Institute for Artificial Intelligence {``}Mihai Dr{\u{a}}g{\u{a}}nescu{''} of the Romanian Academy (RACAI for short).

named-entity-recognition Named Entity Recognition +2

MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language

no code implementations WS 2019 Maria Mitrofan, Verginica Barbu Mititelu, Grigorina Mitrofan

In an era when large amounts of data are generated daily in various fields, the biomedical field among others, linguistic resources can be exploited for various tasks of Natural Language Processing.

Hear about Verbal Multiword Expressions in the Bulgarian and the Romanian Wordnets Straight from the Horse's Mouth

no code implementations WS 2019 Verginica Barbu Mititelu, Ivelina Stoyanova, Svetlozara Leseva, Maria Mitrofan, Tsvetana Dimitrova, Maria Todorova

The contribution of this work is in outlining essential features of the description and classification of VMWEs and the cross-language comparison at the lexical level, which is essential for the understanding of the need for uniform annotation guidelines and a viable procedure for validation of the annotation.

Classification General Classification

Bootstrapping a Romanian Corpus for Medical Named Entity Recognition

no code implementations RANLP 2017 Maria Mitrofan

Named Entity Recognition (NER) is an important component of natural language processing (NLP), with applicability in biomedical domain, enabling knowledge-discovery from medical texts.

Medical Named Entity Recognition named-entity-recognition +4

Adapting the TTL Romanian POS Tagger to the Biomedical Domain

no code implementations RANLP 2017 Maria Mitrofan, Radu Ion

This paper presents the adaptation of the Hidden Markov Models-based TTL part-of-speech tagger to the biomedical domain.

Chunking Domain Adaptation +9

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