Search Results for author: Andr{\'e} Freitas

Found 14 papers, 1 papers with code

STAR: Cross-modal [STA]tement [R]epresentation for selecting relevant mathematical premises

no code implementations EACL 2021 Deborah Ferreira, Andr{\'e} Freitas

Mathematical statements written in natural language are usually composed of two different modalities: mathematical elements and natural language.

Premise Selection in Natural Language Mathematical Texts

no code implementations ACL 2020 Deborah Ferreira, Andr{\'e} Freitas

The discovery of supporting evidence for addressing complex mathematical problems is a semantically challenging task, which is still unexplored in the field of natural language processing for mathematical text.

Link Prediction

DisSim: A Discourse-Aware Syntactic Text Simplification Framework for English and German

no code implementations WS 2019 Christina Niklaus, Matthias Cetto, Andr{\'e} Freitas, H, Siegfried schuh

We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.

Sentence Text Simplification

SemEval-2017 Task 11: End-User Development using Natural Language

no code implementations SEMEVAL 2017 Juliano Sales, H, Siegfried schuh, Andr{\'e} Freitas

This task proposes a challenge to support the interaction between users and applications, micro-services and software APIs using natural language.

Semantic Parsing

SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News

no code implementations SEMEVAL 2017 Keith Cortis, Andr{\'e} Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, H, Siegfried schuh, Brian Davis

This paper discusses the {``}Fine-Grained Sentiment Analysis on Financial Microblogs and News{''} task as part of SemEval-2017, specifically under the {``}Detecting sentiment, humour, and truth{''} theme.

Sentiment Analysis

Categorization of Semantic Roles for Dictionary Definitions

no code implementations WS 2016 Vivian Silva, H, Siegfried schuh, Andr{\'e} Freitas

Understanding the semantic relationships between terms is a fundamental task in natural language processing applications.

Question Answering

NNBlocks: A Deep Learning Framework for Computational Linguistics Neural Network Models

no code implementations LREC 2016 Frederico Tommasi Caroli, Andr{\'e} Freitas, Jo{\~a}o Carlos Pereira da Silva, H, Siegfried schuh

Lately, with the success of Deep Learning techniques in some computational linguistics tasks, many researchers want to explore new models for their linguistics applications.

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