50 Search Results for "Declerck, Thierry"

Volume

OASIcs, Volume 93

3rd Conference on Language, Data and Knowledge (LDK 2021)

LDK 2021, September 1-3, 2021, Zaragoza, Spain

Editors: Dagmar Gromann, Gilles Sérasset, Thierry Declerck, John P. McCrae, Jorge Gracia, Julia Bosque-Gil, Fernando Bobillo, and Barbara Heinisch

Document
Survey
DOI: 10.4230/TGDK.4.1.2
Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support

Authors: Oleksandra Bruns, Jörg Waitelonis, Jeff Z. Pan, and Harald Sack

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract
Our culture, history and world are in constant motion, continuously shaped by the flow of time, evolving narratives, and shifting relationships. Capturing this temporal complexity within cultural heritage (CH) knowledge graphs is essential for preserving the dynamic nature of human heritage. However, standard RDF predicates fail to effectively model the temporal aspects of cultural data, such as changing facts, evolving relationships, and temporal concepts. Over the past two decades, a variety of RDF-based approaches have been proposed to address this limitation, yet guidance is missing on which method best suits specific CH contexts. This paper presents a systematic evaluation of temporal RDF modelling approaches from a CH perspective. Based on an analysis of real-world CH use cases, core temporal requirements are identified that reflect both modelling expressivity and practical concerns. Six prominent approaches - RDF*, tRDF, Named Graphs, Singleton Property, N-ary Relations, and 4D Fluents - are assessed across these requirements. Our findings reveal that no single solution fits all scenarios, but suitable approaches can be selected based on project-specific priorities. To support practitioners, a decision-support tool is introduced to guide them in selecting the most suitable extension for their specific needs. This work provides practical guidance for CH modelling and contributes to the broader development of temporally aware Linked Data.
Cite as

Oleksandra Bruns, Jörg Waitelonis, Jeff Z. Pan, and Harald Sack. Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 2:1-2:46, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{bruns_et_al:TGDK.4.1.2,
  author =	{Bruns, Oleksandra and Waitelonis, J\"{o}rg and Pan, Jeff Z. and Sack, Harald},
  title =	{{Temporal Modelling in Cultural Heritage Knowledge Graphs: Use Cases, Requirements, Evaluation, and Decision Support}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:46},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.2},
  URN =		{urn:nbn:de:0030-drops-256871},
  doi =		{10.4230/TGDK.4.1.2},
  annote =	{Keywords: Temporal Data Representation, RDF Extensions, Cultural Heritage, Knowledge Graphs}
}
Document
Research
DOI: 10.4230/TGDK.3.3.4
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.
Cite as

Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
DOI: 10.4230/TGDK.2.3.1
Unified Multimedia Segmentation - A Comprehensive Model for URI-based Media Segment Representation

Authors: Jan Willi, Abraham Bernstein, and Luca Rossetto

Published in: TGDK, Volume 2, Issue 3 (2024). Transactions on Graph Data and Knowledge, Volume 2, Issue 3

Abstract
In multimedia annotation, referencing specific segments of a document is often desired due to its richness and multimodality, but no universal representation for such references exists. This significantly hampers the usage of multimedia content in knowledge graphs, as it is modeled as one large atomic information container. Unstructured data - such as text, audio, images, and video - can commonly be decomposed into its constituent parts, as such documents rarely contain only one semantic concept. Hence, it is reasonable to assume that these advances will make it possible to decompose these previous atomic components into logical segments. To be processable by the knowledge graph stack, however, one needs to break the atomic nature of multimedia content, providing a mechanism to address media segments. This paper proposes a Unified Segmentation Model capable of depicting arbitrary segmentations on any media document type. The work begins with a formal analysis of multimedia and segmentation, exploring segmentation operations and how to describe them. Building on this analysis, it then develops a practical scheme for expressing segmentation in Uniform Resource Identifiers (URIs). Given that this approach makes segments of multimedia content referencable, it breaks their atomic nature and makes them first-class citizens within knowledge graphs. The proposed model is implemented as a proof of concept in the MediaGraph Store, a multimedia knowledge graph storage and querying engine.
Cite as

Jan Willi, Abraham Bernstein, and Luca Rossetto. Unified Multimedia Segmentation - A Comprehensive Model for URI-based Media Segment Representation. In Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 3, pp. 1:1-1:34, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{willi_et_al:TGDK.2.3.1,
  author =	{Willi, Jan and Bernstein, Abraham and Rossetto, Luca},
  title =	{{Unified Multimedia Segmentation - A Comprehensive Model for URI-based Media Segment Representation}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:34},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.3.1},
  URN =		{urn:nbn:de:0030-drops-225953},
  doi =		{10.4230/TGDK.2.3.1},
  annote =	{Keywords: Multimodal Knowledge Graphs, Multimedia Segmentation, Multimedia Representation}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.10
Multilingual Knowledge Graphs and Low-Resource Languages: A Review

Authors: Lucie-Aimée Kaffee, Russa Biswas, C. Maria Keet, Edlira Kalemi Vakaj, and Gerard de Melo

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
There is a lack of multilingual data to support applications in a large number of languages, especially for low-resource languages. Knowledge graphs (KG) could contribute to closing the gap of language support by providing easily accessible, machine-readable, multilingual linked data, which can be reused across applications. In this paper, we provide an overview of work in the domain of multilingual KGs with a focus on low-resource languages. We review the current state of multilingual KGs along with the different aspects that are crucial for creating KGs with language coverage in mind. Special consideration is given to challenges particular to low-resource languages in KGs. We further provide an overview of applications that yield multilingual KG information as well as downstream applications reusing such multilingual data. Finally, we explore open problems regarding multilingual KGs with a focus on low-resource languages.
Cite as

Lucie-Aimée Kaffee, Russa Biswas, C. Maria Keet, Edlira Kalemi Vakaj, and Gerard de Melo. Multilingual Knowledge Graphs and Low-Resource Languages: A Review. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 10:1-10:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{kaffee_et_al:TGDK.1.1.10,
  author =	{Kaffee, Lucie-Aim\'{e}e and Biswas, Russa and Keet, C. Maria and Vakaj, Edlira Kalemi and de Melo, Gerard},
  title =	{{Multilingual Knowledge Graphs and Low-Resource Languages: A Review}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{10:1--10:19},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.10},
  URN =		{urn:nbn:de:0030-drops-194845},
  doi =		{10.4230/TGDK.1.1.10},
  annote =	{Keywords: knowledge graphs, multilingual, low-resource languages, review}
}
Document
Complete Volume
DOI: 10.4230/OASIcs.LDK.2021
OASIcs, Volume 93, LDK 2021, Complete Volume

Authors: Dagmar Gromann, Gilles Sérasset, Thierry Declerck, John P. McCrae, Jorge Gracia, Julia Bosque-Gil, Fernando Bobillo, and Barbara Heinisch

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
OASIcs, Volume 93, LDK 2021, Complete Volume
Cite as

3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 1-516, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@Proceedings{gromann_et_al:OASIcs.LDK.2021,
  title =	{{OASIcs, Volume 93, LDK 2021, Complete Volume}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{1--516},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021},
  URN =		{urn:nbn:de:0030-drops-145352},
  doi =		{10.4230/OASIcs.LDK.2021},
  annote =	{Keywords: OASIcs, Volume 93, LDK 2021, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/OASIcs.LDK.2021.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Dagmar Gromann, Gilles Sérasset, Thierry Declerck, John P. McCrae, Jorge Gracia, Julia Bosque-Gil, Fernando Bobillo, and Barbara Heinisch

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

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

3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 0:i-0:xvi, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{gromann_et_al:OASIcs.LDK.2021.0,
  author =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{0:i--0:xvi},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.0},
  URN =		{urn:nbn:de:0030-drops-145364},
  doi =		{10.4230/OASIcs.LDK.2021.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
DOI: 10.4230/OASIcs.LDK.2021.1
The JeuxDeMots Project (Invited Talk)

Authors: Mathieu Lafourcade

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
The JeuxDeMots project aims at building a very large knowledge base in French, both common sense and specialized, using games, contributory approaches, and inference mechanisms. A dozen games have been designed as part of this project, each one allowing to collect specific information, or to consolidate the information acquired through the other games. With this presentation, the data collected and constructed since the launch of the project in the summer of 2007 will be analyzed both qualitatively and quantitatively. In particular, the following aspects will be detailed: the structure of the lexical and semantic network, some types of relations (semantic, ontological, subjective, semantic roles, associations of ideas), annotation of relations (meta-information), semantic refinements (management of polysemy), the creation of clusters allowing the representation of richer knowledge (n-argument relations) that make an implicit neural network. Finally, I will describe some complementary acquisition methods and applications such as a bot for endogenous contributions, a chatbot making inferences and semantic extraction from texts.
Cite as

Mathieu Lafourcade. The JeuxDeMots Project (Invited Talk). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{lafourcade:OASIcs.LDK.2021.1,
  author =	{Lafourcade, Mathieu},
  title =	{{The JeuxDeMots Project}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{1:1--1:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.1},
  URN =		{urn:nbn:de:0030-drops-145377},
  doi =		{10.4230/OASIcs.LDK.2021.1},
  annote =	{Keywords: Lexical Semantic Network, Games with a Purpose, Inferences, Knowledge Representation, Semantic Representation}
}
Document
Invited Talk
DOI: 10.4230/OASIcs.LDK.2021.2
A Smell is Worth a Thousand Words: Olfactory Information Extraction and Semantic Processing in a Multilingual Perspective (Invited Talk)

Authors: Sara Tonelli

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
More than any other sense, smell is linked directly to our emotions and our memories. However, smells are intangible and very difficult to preserve, making it hard to effectively identify, consolidate, and promote the wide-ranging role scents and smelling have in our cultural heritage. While some novel approaches have been recently proposed to monitor so-called urban smellscapes and analyse the olfactory dimension of our environments (Quercia et al., 2015), when it comes to smellscapes from the past little research has been done to keep track of how places, events and people have been described from an olfactory perspective. Fortunately, some key prerequisites for addressing this problem are now in place. In recent years, European cultural heritage institutions have invested heavily in large-scale digitisation: we hold a wealth of object, text and image data which can now be analysed using artificial intelligence. What remains missing is a methodology for the extraction of scent-related information from large amounts of texts, as well as a broader awareness of the wealth of historical olfactory descriptions, experiences and memories contained within the heritage datasets. In this talk, I will describe ongoing activities towards this goal, focused on text mining and semantic processing of olfactory information. I will present the general framework designed to annotate smell events in documents, and some preliminary results on information extraction approaches in a multilingual scenario. I will discuss the main findings and the challenges related to modelling textual descriptions of smells, including the metaphorical use of smell-related terms and the well-known limitations of smell vocabulary in European languages compared to other senses.
Cite as

Sara Tonelli. A Smell is Worth a Thousand Words: Olfactory Information Extraction and Semantic Processing in a Multilingual Perspective (Invited Talk). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, p. 2:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{tonelli:OASIcs.LDK.2021.2,
  author =	{Tonelli, Sara},
  title =	{{A Smell is Worth a Thousand Words: Olfactory Information Extraction and Semantic Processing in a Multilingual Perspective}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{2:1--2:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.2},
  URN =		{urn:nbn:de:0030-drops-145386},
  doi =		{10.4230/OASIcs.LDK.2021.2},
  annote =	{Keywords: olfactory information extraction, smellscapes, multilingual annotation}
}
Document
Invited Talk
DOI: 10.4230/OASIcs.LDK.2021.3
Free/Open-Source Machine Translation for the Low-Resource Languages of Spain (Invited Talk)

Authors: Mikel L. Forcada

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
While machine translation has historically been rule-based, that is, based on dictionaries and rules written by experts, most present-day machine translation is corpus-based. In the last few years, statistical machine translation, the dominant corpus-based approach, has been displaced by neural machine translation in most applications, in view of the better results reported, particularly for languages with very different syntax. But both statistical and neural machine translation need to be trained on large amounts of parallel data, that is, sentences in one language carefully paired with their translations in their other language, and this is a resource that may not be available for some low-resource languages. While some of the languages of Spain may be considered to be reasonably endowed with parallel corpora connecting them to Spanish or even to English - Basque, Catalan, Galician -, and are well-served with machine translation systems, there are many other languages which cannot afford them such as Aranese Occitan, Aragonese, or Asturian/Leonese. Fortunately, languages in this last group belong to the Romance language family, as Spanish does, and this makes translation from and into Spanish under a rule-based paradigm the only feasible approach. After describing briefly the main machine translation paradigms, I will describe the Apertium free/open-source rule-based machine translation platform, which has been used to build machine translation systems for these low-resource languages of Spain, indeed, sometimes the only ones available. The free/open-source setting has made linguistic data for these languages available for anyone in their linguistic communities to build other linguistic technologies for these low-resourced languages. For example, the Apertium family of bilingual and monolingual data has been converted into RDF and they have been made accessible on the Web as linked data.
Cite as

Mikel L. Forcada. Free/Open-Source Machine Translation for the Low-Resource Languages of Spain (Invited Talk). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, p. 3:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{forcada:OASIcs.LDK.2021.3,
  author =	{Forcada, Mikel L.},
  title =	{{Free/Open-Source Machine Translation for the Low-Resource Languages of Spain}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{3:1--3:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.3},
  URN =		{urn:nbn:de:0030-drops-145399},
  doi =		{10.4230/OASIcs.LDK.2021.3},
  annote =	{Keywords: free/open-source, machine translation, languages of Spain, low-resource machine translation}
}
Document
Crazy New Idea
DOI: 10.4230/OASIcs.LDK.2021.4
A Computational Simulation of Children’s Language Acquisition (Crazy New Idea)

Authors: Ben Ambridge

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
Many modern NLP models are already close to simulating children’s language acquisition; the main thing they currently lack is a "real world" representation of semantics that allows them to map from form to meaning and vice-versa. The aim of this "Crazy Idea" is to spark a discussion about how we might get there.
Cite as

Ben Ambridge. A Computational Simulation of Children’s Language Acquisition (Crazy New Idea). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 4:1-4:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{ambridge:OASIcs.LDK.2021.4,
  author =	{Ambridge, Ben},
  title =	{{A Computational Simulation of Children’s Language Acquisition}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{4:1--4:3},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.4},
  URN =		{urn:nbn:de:0030-drops-145402},
  doi =		{10.4230/OASIcs.LDK.2021.4},
  annote =	{Keywords: Child language acquisition, language development, deep learning, BERT, ELMo, GPT-3}
}
Document
Crazy New Idea
DOI: 10.4230/OASIcs.LDK.2021.5
Get! Mimetypes! Right! (Crazy New Idea)

Authors: Christian Chiarcos

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
This paper identifies three technical requirements - availability of data, sustainable hosting and resolvable URIs for hosted data - as minimal pre-conditions for Linguistic Linked Open Data technology to develop towards a mature technological ecosystem that third party applications can build upon. While a critical amount of data is available (and it continues to grow), there does not seem to exist a hosting solution that combines the prospects of long-term availability with an unrestricted capability to support resolvable URIs. In particular, data hosting services do currently not allow data to be declared as RDF content by means of their media type (mime type), so that the capability of clients to recognize formats and to resolve URIs on that basis is severely limited.
Cite as

Christian Chiarcos. Get! Mimetypes! Right! (Crazy New Idea). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 5:1-5:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{chiarcos:OASIcs.LDK.2021.5,
  author =	{Chiarcos, Christian},
  title =	{{Get! Mimetypes! Right!}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{5:1--5:4},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.5},
  URN =		{urn:nbn:de:0030-drops-145418},
  doi =		{10.4230/OASIcs.LDK.2021.5},
  annote =	{Keywords: data hosting, mimetypes, resolvability, URIs, Linked Data foundations}
}
Document
Crazy New Idea
DOI: 10.4230/OASIcs.LDK.2021.6
Mind the Gap: Language Data, Their Producers, and the Scientific Process (Crazy New Idea)

Authors: Tobias Weber

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
This paper discusses the role of low-resource languages in NLP through the lens of different stakeholders. It argues that the current "consumerist approach" to language data reinforces a vicious circle which increases the technological exclusion of minority communities. Researchers' decisions directly affect these processes to the detriment of minorities and practitioners engaging in language work in these communities. In line with the conference topic, the paper concludes with strategies and prerequisites for creating a positive feedback loop in our research benefiting language work within the next decade.
Cite as

Tobias Weber. Mind the Gap: Language Data, Their Producers, and the Scientific Process (Crazy New Idea). In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 6:1-6:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{weber:OASIcs.LDK.2021.6,
  author =	{Weber, Tobias},
  title =	{{Mind the Gap: Language Data, Their Producers, and the Scientific Process}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{6:1--6:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.6},
  URN =		{urn:nbn:de:0030-drops-145424},
  doi =		{10.4230/OASIcs.LDK.2021.6},
  annote =	{Keywords: minority languages, data integration, sociology of technology, documentary linguistics, exclusion}
}
Document
DOI: 10.4230/OASIcs.LDK.2021.7
Representing the Under-Represented: a Dataset of Post-Colonial, and Migrant Writers

Authors: Marco Antonio Stranisci, Viviana Patti, and Rossana Damiano

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
In today’s media and in the Web of Data, non-Western people still suffer a lack of representation. In our work, we address this issue by presenting a pipeline for collecting and semantically encoding Wikipedia biographies of writers who are under-represented due to their non-Western origins, or their legal status in a country. The two main components of the ontology will be described, together with a framework for mapping textual biographies to their corresponding semantic representations. A description of the data set, and some examples of biographical texts conversion to the Ontology Classes, will be provided.
Cite as

Marco Antonio Stranisci, Viviana Patti, and Rossana Damiano. Representing the Under-Represented: a Dataset of Post-Colonial, and Migrant Writers. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{stranisci_et_al:OASIcs.LDK.2021.7,
  author =	{Stranisci, Marco Antonio and Patti, Viviana and Damiano, Rossana},
  title =	{{Representing the Under-Represented: a Dataset of Post-Colonial, and Migrant Writers}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{7:1--7:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.7},
  URN =		{urn:nbn:de:0030-drops-145431},
  doi =		{10.4230/OASIcs.LDK.2021.7},
  annote =	{Keywords: Ontologies, Knowledge Graph, Language Resources, Migrations}
}
Document
DOI: 10.4230/OASIcs.LDK.2021.8
Plenary Debates of the Parliament of Finland as Linked Open Data and in Parla-CLARIN Markup

Authors: Laura Sinikallio, Senka Drobac, Minna Tamper, Rafael Leal, Mikko Koho, Jouni Tuominen, Matti La Mela, and Eero Hyvönen

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
This paper presents a knowledge graph created by transforming the plenary debates of the Parliament of Finland (1907-) into Linked Open Data (LOD). The data, totaling over νm{900 000} speeches, with automatically created semantic annotations and rich ontology-based metadata, are published in a Linked Open Data Service and are used via a SPARQL API and as data dumps. The speech data is part of larger LOD publication FinnParla that also includes prosopographical data about the politicians. The data is being used for studying parliamentary language and culture in Digital Humanities in several universities. To serve a wider variety of users, the entirety of this data was also produced using Parla-CLARIN markup. We present the first publication of all Finnish parliamentary debates as data. Technical novelties in our approach include the use of both Parla-CLARIN and an RDF schema developed for representing the speeches, integration of the data to a new Parliament of Finland Ontology for deeper data analyses, and enriching the data with a variety of external national and international data sources.
Cite as

Laura Sinikallio, Senka Drobac, Minna Tamper, Rafael Leal, Mikko Koho, Jouni Tuominen, Matti La Mela, and Eero Hyvönen. Plenary Debates of the Parliament of Finland as Linked Open Data and in Parla-CLARIN Markup. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 8:1-8:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{sinikallio_et_al:OASIcs.LDK.2021.8,
  author =	{Sinikallio, Laura and Drobac, Senka and Tamper, Minna and Leal, Rafael and Koho, Mikko and Tuominen, Jouni and La Mela, Matti and Hyv\"{o}nen, Eero},
  title =	{{Plenary Debates of the Parliament of Finland as Linked Open Data and in Parla-CLARIN Markup}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{8:1--8:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.8},
  URN =		{urn:nbn:de:0030-drops-145444},
  doi =		{10.4230/OASIcs.LDK.2021.8},
  annote =	{Keywords: Plenary debates, parliamentary data, Parla-CLARIN, Linked Open Data, Digital Humanities}
}
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