95 Search Results for "Portela, Filipe"


Volume

OASIcs, Volume 113

12th Symposium on Languages, Applications and Technologies (SLATE 2023)

SLATE 2023, June 26-28, 2023, Vila do Conde, Portugal

Editors: Alberto Simões, Mario Marcelo Berón, and Filipe Portela

Volume

OASIcs, Volume 94

10th Symposium on Languages, Applications and Technologies (SLATE 2021)

SLATE 2021, July 1-2, 2021, Vila do Conde/Póvoa de Varzim, Portugal

Editors: Ricardo Queirós, Mário Pinto, Alberto Simões, Filipe Portela, and Maria João Pereira

Volume

OASIcs, Volume 91

Second International Computer Programming Education Conference (ICPEC 2021)

ICPEC 2021, May 27-28, 2021, University of Minho, Braga, Portugal

Editors: Pedro Rangel Henriques, Filipe Portela, Ricardo Queirós, and Alberto Simões

Volume

OASIcs, Volume 81

First International Computer Programming Education Conference (ICPEC 2020)

ICPEC 2020, June 25-26, 2020, ESMAD, Vila do Conde, Portugal (Virtual Conference)

Editors: Ricardo Queirós, Filipe Portela, Mário Pinto, and Alberto Simões

Document
Complete Volume
OASIcs, Volume 113, SLATE 2023, Complete Volume

Authors: Alberto Simões, Mario Marcelo Berón, and Filipe Portela

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
OASIcs, Volume 113, SLATE 2023, Complete Volume

Cite as

12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 1-206, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@Proceedings{simoes_et_al:OASIcs.SLATE.2023,
  title =	{{OASIcs, Volume 113, SLATE 2023, Complete Volume}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{1--206},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023},
  URN =		{urn:nbn:de:0030-drops-185130},
  doi =		{10.4230/OASIcs.SLATE.2023},
  annote =	{Keywords: OASIcs, Volume 113, SLATE 2023, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Alberto Simões, Mario Marcelo Berón, and Filipe Portela

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 0:i-0:xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{simoes_et_al:OASIcs.SLATE.2023.0,
  author =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{0:i--0:xii},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.0},
  URN =		{urn:nbn:de:0030-drops-185141},
  doi =		{10.4230/OASIcs.SLATE.2023.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Question Answering over Linked Data with GPT-3

Authors: Bruno Faria, Dylan Perdigão, and Hugo Gonçalo Oliveira

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
This paper explores GPT-3 for answering natural language questions over Linked Data. Different engines of the model and different approaches are adopted for answering questions in the QALD-9 dataset, namely: zero and few-shot SPARQL generation, as well as fine-tuning in the training portion of the dataset. Answers retrieved by the generated queries and answers generated directly by the model are also compared. Overall results are generally poor, but several insights are provided on using GPT-3 for the proposed task.

Cite as

Bruno Faria, Dylan Perdigão, and Hugo Gonçalo Oliveira. Question Answering over Linked Data with GPT-3. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{faria_et_al:OASIcs.SLATE.2023.1,
  author =	{Faria, Bruno and Perdig\~{a}o, Dylan and Gon\c{c}alo Oliveira, Hugo},
  title =	{{Question Answering over Linked Data with GPT-3}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{1:1--1:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.1},
  URN =		{urn:nbn:de:0030-drops-185155},
  doi =		{10.4230/OASIcs.SLATE.2023.1},
  annote =	{Keywords: SPARQL Generation, Prompt Engineering, Few-Shot Learning, Question Answering, GPT-3}
}
Document
A Framework for Fostering Easier Access to Enriched Textual Information

Authors: Gabriel Silva, Mário Rodrigues, António Teixeira, and Marlene Amorim

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
Considering the amount of information in unstructured data it is necessary to have suitable methods to extract information from it. Most of these methods have their own output making it difficult and costly to merge and share this information as there currently is no unified way of representing this information. While most of these methods rely on JSON or XML there has been a push to serialize these into RDF compliant formats due to their flexiblity and the existing ecosystem surrounding them. In this paper we introduce a framework whose goal is to provide a serialization of enriched data into an RDF format, following FAIR principles, making it more interpretable, interoperable and shareable. We process a subset of the WikiNER dataset and showcase two examples of using this framework: One using CoNLL annotations and the other by performing entity-linking on an already existing graph. The results are a graph with every connection starting from the document and finishing on tokens while keeping the original text intact while embedding the enriched data into it, in this case the CoNLL annotations and Entities.

Cite as

Gabriel Silva, Mário Rodrigues, António Teixeira, and Marlene Amorim. A Framework for Fostering Easier Access to Enriched Textual Information. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{silva_et_al:OASIcs.SLATE.2023.2,
  author =	{Silva, Gabriel and Rodrigues, M\'{a}rio and Teixeira, Ant\'{o}nio and Amorim, Marlene},
  title =	{{A Framework for Fostering Easier Access to Enriched Textual Information}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{2:1--2:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.2},
  URN =		{urn:nbn:de:0030-drops-185165},
  doi =		{10.4230/OASIcs.SLATE.2023.2},
  annote =	{Keywords: Knowledge graphs, Enriched data, Natural language processing, Triplestore}
}
Document
A Pseudonymization Prototype for Hungarian

Authors: Attila Novák and Borbála Novák

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
In this paper, we present a pseudonymization prototype for Hungarian, an agglutinating language with complex morphology, implemented as a web service. The service provides the following functions: entity identification and extraction; automatic generation and selection of replacement candidates; automatic and consistent replacement and reinflection of entities in the final pseudonymized document. The named entity recognition model applied handles names of persons well, and it has decent performance on other entity types as well. However ID-like entities need to be handled separately to achieve proper performance (not handled in the current prototype version). For automatic replacement candidate generation, a simple entity embedding model is used. We discuss the performance and limitations of the prototype in detail.

Cite as

Attila Novák and Borbála Novák. A Pseudonymization Prototype for Hungarian. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 3:1-3:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{novak_et_al:OASIcs.SLATE.2023.3,
  author =	{Nov\'{a}k, Attila and Nov\'{a}k, Borb\'{a}la},
  title =	{{A Pseudonymization Prototype for Hungarian}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{3:1--3:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.3},
  URN =		{urn:nbn:de:0030-drops-185177},
  doi =		{10.4230/OASIcs.SLATE.2023.3},
  annote =	{Keywords: named entity recognition, morphological reinflection, pseudonymization, entity embedding model}
}
Document
Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese

Authors: Hugo Gonçalo Oliveira, Igor Caetano, Renato Matos, and Hugo Amaro

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
In the process of multiple-choice question generation, different methods are often considered for distractor acquisition, as an attempt to cover as many questions as possible. Some, however, result in many candidate distractors of variable quality, while only three or four are necessary. We implement some distractor generation methods for Portuguese and propose their combination and ranking with language models. Experimentation results confirm that this increases both coverage and suitability of the selected distractors.

Cite as

Hugo Gonçalo Oliveira, Igor Caetano, Renato Matos, and Hugo Amaro. Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 4:1-4:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{goncalooliveira_et_al:OASIcs.SLATE.2023.4,
  author =	{Gon\c{c}alo Oliveira, Hugo and Caetano, Igor and Matos, Renato and Amaro, Hugo},
  title =	{{Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{4:1--4:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.4},
  URN =		{urn:nbn:de:0030-drops-185185},
  doi =		{10.4230/OASIcs.SLATE.2023.4},
  annote =	{Keywords: Multiple-Choice Questions, Distractor Generation, Language Models}
}
Document
Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations

Authors: David Rodrigues, António L. Lopes, and Fernando Batista

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
The number of citations a research paper receives is a crucial metric for both researchers and institutions. However, since citation databases have their own source lists, finding all the citations of a given paper can be a challenge. As a result, there may be missing citations that are not counted towards a paper’s total citation count. To address this issue, we present an automated approach to find missing citations leveraging the use of multiple indexing databases. In this research, Web of Science (WoS) serves as a case study and OpenAlex is used as a reference point for comparison. For a given paper, we identify all citing papers found in both research databases. Then, for each citing paper we check if it is indexed in WoS, but not referred in WoS as a citing paper, in order to determine if it is a missing citation. In our experiments, from a set of 1539 papers indexed by WoS, we found 696 missing citations. This outcome proves the success of our approach, and reveals that WoS does not always consider the full list of citing papers of a given publication, even when these citing papers are indexed by WoS. We also found that WoS has a higher chance of missing information for more recent publications. These findings provide relevant insights about this indexing research database, and provide enough motivation for considering other research databases in our study, such as Scopus and Google Scholar, in order to improve the matching and querying algorithms, and to reduce false positives, towards providing a more comprehensive and accurate view of the citations of a paper.

Cite as

David Rodrigues, António L. Lopes, and Fernando Batista. Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 5:1-5:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{rodrigues_et_al:OASIcs.SLATE.2023.5,
  author =	{Rodrigues, David and Lopes, Ant\'{o}nio L. and Batista, Fernando},
  title =	{{Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{5:1--5:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.5},
  URN =		{urn:nbn:de:0030-drops-185199},
  doi =		{10.4230/OASIcs.SLATE.2023.5},
  annote =	{Keywords: Research Databases, Citations, Citation Databases, Web of Science, OpenAlex}
}
Document
Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge

Authors: Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
We are extending the keyword-based query interface DdQl for relational databases which is based on contextual background knowledge such as suitable join conditions and which was proposed in [{Dietmar Seipel, 2021]. In the previous paper, join conditions were extracted from existing referential integrity (foreign key) constraints of the database schema, or they could be learned from other, previous database queries. In this paper, we describe a speech-to-text component for entering the query keywords based on the system Whisper. Keywords, which have been recognized wrongly by Whisper can be corrected to similarly sounding words. Again, the context of the database schema can help here. For users with a limited knowledge of the schema and the contents of the database, the approach of DdQl can help to provide useful suggestions for query implementations in Sql or Datalog, from which the user can choose one. Our tool DdQl can be run in a docker image; it yields the possible queries in Sql and a special domain specific rule language that extends Datalog. The Datalog variant allows for additional user-defined aggregation functions which are not possible in Sql.

Cite as

Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu. Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 6:1-6:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{seipel_et_al:OASIcs.SLATE.2023.6,
  author =	{Seipel, Dietmar and F\"{o}rster, Benjamin and Liebl, Magnus and Waleska, Marcel and Abreu, Salvador},
  title =	{{Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{6:1--6:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.6},
  URN =		{urn:nbn:de:0030-drops-185202},
  doi =		{10.4230/OASIcs.SLATE.2023.6},
  annote =	{Keywords: Knowledge Bases, Natural Language Interface, Logic Programming, Definite Clause Grammars, Referential Integrity Constraints, Speech-to-Text}
}
Document
Short Paper
Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications (Short Paper)

Authors: Simone Wills, Yu Bai, Cristian Tejedor-García, Catia Cucchiarini, and Helmer Strik

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
Voicebots have provided a new avenue for supporting the development of language skills, particularly within the context of second language learning. Voicebots, though, have largely been geared towards native adult speakers. We sought to assess the performance of two state-of-the-art ASR systems, Wav2Vec2.0 and Whisper AI, with a view to developing a voicebot that can support children acquiring a foreign language. We evaluated their performance on read and extemporaneous speech of native and non-native Dutch children. We also investigated the utility of using ASR technology to provide insight into the children’s pronunciation and fluency. The results show that recent, pre-trained ASR transformer-based models achieve acceptable performance from which detailed feedback on phoneme pronunciation quality can be extracted, despite the challenging nature of child and non-native speech.

Cite as

Simone Wills, Yu Bai, Cristian Tejedor-García, Catia Cucchiarini, and Helmer Strik. Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications (Short Paper). In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 7:1-7:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{wills_et_al:OASIcs.SLATE.2023.7,
  author =	{Wills, Simone and Bai, Yu and Tejedor-Garc{\'\i}a, Cristian and Cucchiarini, Catia and Strik, Helmer},
  title =	{{Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{7:1--7:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.7},
  URN =		{urn:nbn:de:0030-drops-185218},
  doi =		{10.4230/OASIcs.SLATE.2023.7},
  annote =	{Keywords: Automatic Speech Recognition, ASR, Child Speech, Non-Native Speech, Human-computer Interaction, Whisper, Wav2Vec2.0}
}
Document
OCRticle - a Structure-Aware OCR Application

Authors: Sofia G. Rodrigues dos Santos and J. João Dias de Almeida

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
While there are currently many applications and websites capable of performing Optical Character Recognition (OCR), none of the widely available options offer structured OCR, i.e., OCR that maintains the text’s original structure. For example, if a document has a title, after performing OCR on it, the title should have a different formatting, in order to distinguish it from the rest of the text. This paper covers the topic of structure-aware OCR, first by describing the current state of OCR tools, then by showcasing a prototype tool capable of retaining the structure of articles scanned from an image.

Cite as

Sofia G. Rodrigues dos Santos and J. João Dias de Almeida. OCRticle - a Structure-Aware OCR Application. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 8:1-8:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{rodriguesdossantos_et_al:OASIcs.SLATE.2023.8,
  author =	{Rodrigues dos Santos, Sofia G. and Dias de Almeida, J. Jo\~{a}o},
  title =	{{OCRticle - a Structure-Aware OCR Application}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{8:1--8:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.8},
  URN =		{urn:nbn:de:0030-drops-185220},
  doi =		{10.4230/OASIcs.SLATE.2023.8},
  annote =	{Keywords: OCR, Optical Character Recognition, Data Structure, Data Parsing, Document Structure}
}
Document
Short Paper
Narrative Extraction from Semantic Graphs (Short Paper)

Authors: Daniil Lystopadskyi, André Santos, and José Paulo Leal

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)


Abstract
This paper proposes an interactive approach for narrative extraction from semantic graphs. The proposed approach extracts events from RDF triples, maps them to their corresponding attributes, and assembles them into a chronological sequence to form narrative graphs. The approach is evaluated on the Wikidata graph and achieves promising results in terms of narrative quality and coherence. The paper also discusses several avenues for future work, including the integration of machine learning, graph embedding methods and the exploration of advanced techniques for attention-based narrative labeling and semantic role labeling. Overall, the proposed method offers a promising approach to narrative extraction from semantic graphs and has the potential to be useful in various applications, including chatbots, conversational agents, and content creation tools.

Cite as

Daniil Lystopadskyi, André Santos, and José Paulo Leal. Narrative Extraction from Semantic Graphs (Short Paper). In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 9:1-9:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{lystopadskyi_et_al:OASIcs.SLATE.2023.9,
  author =	{Lystopadskyi, Daniil and Santos, Andr\'{e} and Leal, Jos\'{e} Paulo},
  title =	{{Narrative Extraction from Semantic Graphs}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{9:1--9:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.9},
  URN =		{urn:nbn:de:0030-drops-185231},
  doi =		{10.4230/OASIcs.SLATE.2023.9},
  annote =	{Keywords: Narratives, Narrative Extraction, Information Retrieval, Knowledge Graphs, Semantic Graphs, Resource Description Framework, Web Ontology}
}
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