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Documents authored by Gromann, Dagmar


Document
Complete Volume
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

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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
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
Towards Learning Terminological Concept Systems from Multilingual Natural Language Text

Authors: Lennart Wachowiak, Christian Lang, Barbara Heinisch, and Dagmar Gromann

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


Abstract
Terminological Concept Systems (TCS) provide a means of organizing, structuring and representing domain-specific multilingual information and are important to ensure terminological consistency in many tasks, such as translation and cross-border communication. While several approaches to (semi-)automatic term extraction exist, learning their interrelations is vastly underexplored. We propose an automated method to extract terms and relations across natural languages and specialized domains. To this end, we adapt pretrained multilingual neural language models, which we evaluate on term extraction standard datasets with best performing results and a combination of relation extraction standard datasets with competitive results. Code and dataset are publicly available.

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Lennart Wachowiak, Christian Lang, Barbara Heinisch, and Dagmar Gromann. Towards Learning Terminological Concept Systems from Multilingual Natural Language Text. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{wachowiak_et_al:OASIcs.LDK.2021.22,
  author =	{Wachowiak, Lennart and Lang, Christian and Heinisch, Barbara and Gromann, Dagmar},
  title =	{{Towards Learning Terminological Concept Systems from Multilingual Natural Language Text}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{22:1--22:18},
  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.2021.22},
  URN =		{urn:nbn:de:0030-drops-145586},
  doi =		{10.4230/OASIcs.LDK.2021.22},
  annote =	{Keywords: Terminologies, Neural Language Models, Multilingual Information Extraction}
}
Document
Towards the Detection and Formal Representation of Semantic Shifts in Inflectional Morphology

Authors: Dagmar Gromann and Thierry Declerck

Published in: OASIcs, Volume 70, 2nd Conference on Language, Data and Knowledge (LDK 2019)


Abstract
Semantic shifts caused by derivational morphemes is a common subject of investigation in language modeling, while inflectional morphemes are frequently portrayed as semantically more stable. This study is motivated by the previously established observation that inflectional morphemes can be just as variable as derivational ones. For instance, the English plural "-s" can turn the fabric silk into the garments of a jockey, silks. While humans know that silk in this sense has no plural, it takes more for machines to arrive at this conclusion. Frequently utilized computational language resources, such as WordNet, or models for representing computational lexicons, like OntoLex-Lemon, have no descriptive mechanism to represent such inflectional semantic shifts. To investigate this phenomenon, we extract word pairs of different grammatical number from WordNet that feature additional senses in the plural and evaluate their distribution in vector space, i.e., pre-trained word2vec and fastText embeddings. We then propose an extension of OntoLex-Lemon to accommodate this phenomenon that we call inflectional morpho-semantic variation to provide a formal representation accessible to algorithms, neural networks, and agents. While the exact scope of the problem is yet to be determined, this first dataset shows that it is not negligible.

Cite as

Dagmar Gromann and Thierry Declerck. Towards the Detection and Formal Representation of Semantic Shifts in Inflectional Morphology. In 2nd Conference on Language, Data and Knowledge (LDK 2019). Open Access Series in Informatics (OASIcs), Volume 70, pp. 21:1-21:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@InProceedings{gromann_et_al:OASIcs.LDK.2019.21,
  author =	{Gromann, Dagmar and Declerck, Thierry},
  title =	{{Towards the Detection and Formal Representation of Semantic Shifts in Inflectional Morphology}},
  booktitle =	{2nd Conference on Language, Data and Knowledge (LDK 2019)},
  pages =	{21:1--21:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Eskevich, Maria and de Melo, Gerard and F\"{a}th, Christian and McCrae, John P. and Buitelaar, Paul and Chiarcos, Christian and Klimek, Bettina and Dojchinovski, Milan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2019.21},
  URN =		{urn:nbn:de:0030-drops-103856},
  doi =		{10.4230/OASIcs.LDK.2019.21},
  annote =	{Keywords: Inflectional morphology, semantic shift, embeddings, formal lexical modeling}
}