Papers with Portuguese language

6 papers
Semantically Inspired AMR Alignment for the Portuguese Language (2020.emnlp-main)

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Challenge: Abstract Meaning Representation (AMR) parsers require alignment between nodes and words of the sentence.
Approach: They propose to use a more semantically matched word-concept pair to align graphs with words in Portuguese . they performed intrinsic and extrinsic evaluations and found it outperforms the English alignment strategies.
Outcome: The proposed method outperforms the existing methods for English and achieves competitive results with a parser designed for the Portuguese language.
A Multi- versus a Single-classifier Approach for the Identification of Modality in the Portuguese Language (L18-1)

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Challenge: Comparative study of two different approaches to build an automatic classification system for Modality values in the Portuguese language.
Approach: They propose to use a single multi-class classifier with the full Portuguese language dataset that includes eleven modal verbs and a weighted average approach to build different classifiers for each verb.
Outcome: The proposed system is based on a Portuguese language dataset with 11 modal verbs and two different classifiers, one for each verb.
Offensive Video Detection: Dataset and Baseline Results (2020.lrec-1)

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Challenge: a large number of social media platforms discourage users from publishing offensive content . however, there is no method to detect offensive content on these platforms due to the high volume of publications.
Approach: They propose to use text-based machine learning to detect offensive content on different platforms . they use word embedding with Deep Learning classifiers to perform best results .
Outcome: The proposed methods outperform Classic and Deep Learning classifiers in Portuguese and CNN architectures in other features.
Embeddings for Named Entity Recognition in Geoscience Portuguese Literature (2020.lrec-1)

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Challenge: Named Entity Recognition (NER) is a task within the field of Natural Language Processing that deals with the identification and categorization of Named entities (NEs) in a given text.
Approach: They propose to use vector and tensor embeddings to train Portuguese Named Entity Recognition (NER) in the Geology domain.
Outcome: The proposed model achieves state-of-the-art for the Portuguese Geology domain with one of its embeddings.
Universal Grammatical Dependencies for Portuguese with CINTIL Data, LX Processing and CLARIN support (2022.lrec-1)

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Challenge: a new collection of quality language resources is presented for the computational processing of the Portuguese language . the framework for the mapping between linguistic form and meaning is centered on the notion of grammatical relation .
Approach: They propose a new set of quality language resources for the computational processing of the Portuguese language under the Universal Dependencies framework.
Outcome: The proposed framework provides for the mapping between linguistic form and meaning representations.
HateBR: A Large Expert Annotated Corpus of Brazilian Instagram Comments for Offensive Language and Hate Speech Detection (2022.lrec-1)

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Challenge: In Brazil, hate speech is prohibited, however the regulation is not effective due to the difficulty of identifying, quantifying and classifying this kind of online content.
Approach: They propose to annotate a large corpus of Brazilian Instagram comments manually and to use it to detect hate speech and offensive language.
Outcome: The HateBR corpus was collected from the comment section of Brazilian politicians’ accounts on Instagram and manually annotated by specialists, reaching a high inter-annotator agreement.

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