We propose a methodology to populate the verb type hierarchy of a deep computational grammar in the HPSG formalism using syntactic and morphological information from Universal Dependencies (UD) treebanks. It is exemplified by means of the UD Bosque corpus and PorGram, a computational grammar for Portuguese constructed in the LinGO Grammar Matrix framework, but it can be applied to analogous grammars of other languages using other UD treebanks. The main component of the methodology is a Python module that extracts from the annotated sentences the core arguments and other features that are relevant to determine verb valence. This module enables the creation of a Python dictionary that maps valence frames to verb objects. This dictionary facilitates not only determining which frames occur with which verbs, but also detecting annotation errors. The potential of the module for rapid expansion of the lexical coverage of PorGram and corpus annotation error detection is illustrated with concrete examples.

Extracting valences from a dependency treebank for populating the verb lexicon of a Portuguese HPSG grammar

Ampla cobertura lexical constitui um dos pré-requisitos para a robustez de uma gramática computacional. Propomos uma metodologia para povoar a tabela de formas verbais irregulares da PorGram (gramática do português no formalismo HPSG) utilizando os dados do dicionário MorphoBr. Nós implementamos um algoritmo que classifica as formas verbais do MorphoBr em regulares e irregulares, aplicando as regras flexionais da PorGram. Avaliamos o algoritmo com numa amostra de 38 verbos, regulares e irregulares, obtendo os resultados esperados. Uma contribuição adicional foi o melhoramento do MorphoBr, com a eliminação de mais de 270.000 entradas erradas e a inclusão de quase 13.000 entradas faltantes.

Utilizando um Dicionário Morfológico para expandir a cobertura lexical de uma Gramática do Português no formalismo HPSG

Language resources, such as corpora, are fundamental for the development of text processing tools. A resource currently considered fundamental for NLP in Portuguese is the corpus UD Bosque, part of the corpora collection in the Universal Dependencies (UD) project. Despite UD Bosque being originated from a manually revised (golden) corpus, several annotation consistency problems are encountered in its current version. In this work, we present the methodology to correct the problems of morphological annotations in the corpus; in particular, we correct morphological agreements of adjectives, determinants, and nouns. We discuss the errors, exceptions, or non-trivial cases, corrections that we made, and the impact of changes on the corpus on the training of statistical parsers.

Explorando a revisão de corpora por meio da comparação de regras gramaticais em padrões sintáticos

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Poster Session 1

poster

The International Conference on Computational Processing of Portuguese (PROPOR) is the main event in the area of human language processing that is focused on theoretical and technological issues of written and spoken Portuguese and Galician. The meeting has been a very rich forum for the exchange of ideas and partnerships for the research and industry communities dedicated to the automated processing of Portuguese, promoting the development of methodologies, resources and projects that can be shared among researchers and practitioners in the field.

Find more information and pay the registration fee on [event organizer’s website](https://sites.universidadedefortaleza.com/propor2022/?page_id=401)

PROPOR 2022

The International Conference on Computational Processing of Portuguese (PROPOR) is the main event in the area of human language processing that is focused on theoretical and technological issues of written and spoken Portuguese and Galician.

**Chairs:** Evandro Ruiz	and Tiago Torrent




STIL Main Conference Session A: Corpora, Lexicons and Grammars

technical paper

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

To access the 10th Brazilian Conference on Intelligent Systems (**BRACIS**), you need to register for the conference.  Please visit the Conference official site to register

[Register now](http://c4ai.inova.usp.br/bracis2021/)

Register now

BRACIS 2021

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

Alexandre Rademaker

3

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Extracting valences from a dependency treebank for populating the verb lexicon of a Portuguese HPSG grammar

Utilizando um Dicionário Morfológico para expandir a cobertura lexical de uma Gramática do Português no formalismo HPSG

Explorando a revisão de corpora por meio da comparação de regras gramaticais em padrões sintáticos

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