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DL4LD 2023 : 3rd Workshop on Deep Learning, Relation Extraction and Linguistic Data with a Case Study on BATS

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Link: http://dl4ld2023.mruni.eu/
 
When Sep 13, 2023 - Sep 13, 2023
Where Vienna, Austria
Submission Deadline May 19, 2023
Notification Due Jun 16, 2023
Final Version Due Jun 30, 2023
Categories    NLP   computational linguistics   linguistics   artificial intelligence
 

Call For Papers




Call for papers

3rd Workshop DL4LD (Deep Learning, Relation Extraction and Linguistic Data with a Case Study on BATS) as a continuation of the series of DL4LD (Deep Learning and Neural Approaches for Linguistic Linked Data) workshops

University of Vienna, Vienna, Austria

13 September 2023

Website: http://dl4ld2023.mruni.eu/


The fourth biennial conference on Language, Data and Knowledge (LDK 2023) and Cost Action CA18209 NexusLinguarum are glad to announce the 3rd workshop DL4LD (Deep Learning, Relation Extraction and Linguistic Data with a Case Study on BATS): Addressing Deep Learning, Relation Extraction, and Linguistic Data with a Case Study on The Bigger Analogy Test Set (BATS). The workshop will be held in a hybrid mode, so speakers and attendees can choose to participate onsite or online.

Conference aims and topics

The workshop welcomes contributions from scholars and researchers working in computational linguistics, data science, linguistics, computer science, etc. This workshop aims at bringing together relation extraction, deep learning, and neural approaches with linguistic linked data. We invite research papers, application descriptions, system demonstrations, and position papers that discuss the interconnection of both areas. The workshop is going to include a twofold session with the first part focusing on the workshop presentations and the second part poster presentations on the multilingual linguistic data preparation for NLP experiments focusing on the case study of BATS. We suggest the researchers working on related languages join teams and present rich comparative case studies. Panel discussion includes “unorthodox” new ideas, overviews of the challenges and opportunities of multilingual data preparation for the BATS experiment.
The workshop presents an excellent opportunity for the exchange of ideas, insights, and the latest research. The workshop topics are (but not limited to) the following:

Topics:
• Deep Learning for Linguistic Linked (Open) Data, modelling, resources & interlinking
• LLOD and Deep Learning for Digital Humanities
• Enhancement of language models with structured linguistic data
• Use cases combining language models and structured linguistic data
• Deep Learning and LLOD in NLP
• Deep learning and relation extraction
• Deep learning and knowledge graphs
• Multilingual data preparation for the BATS experiment

Deep learning and neural network approaches are indispensable in modern Natural Language Processing and generally in all kinds of linguistic data analysis approaches. Artificial intelligence integrating knowledge is one of the core topics in the current research which focuses on providing human thinking for AI to solve complex tasks. One of the important techniques for supporting this research is knowledge acquisition or so-called relation extraction. Relation extraction and deep learning can serve the understanding of the specificities of linguistic data, to be better exploited and combined with linked data mechanisms. Knowledge is a way of understanding the world, aiming to provide a human-level cognition and intelligence for the next-generation artificial intelligence. One way of knowledge representation is semantic relations between entities. Relation Extraction ensures an effective way to automatically acquire important knowledge of semantic relations. It is a sub-task of information extraction and plays an essential role in Natural Language Processing. Its purpose is to identify semantic relations between entities from natural language text. Concerning the current research, there is a field of studies for relation extraction which have described the techniques based on Deep Neural Networks used as a prevailing technique in the research. The workshop intends to be an event of discussion for researchers interested in addressing the peculiarities of the interrelated research areas mentioned before and in advancing the state of the art in deep learning, relation extraction, and linguistic data science.

Program:

The Scientific Program will include an invited talk and research presentations, followed by the panel discussion.

Invited Speaker:

Michael Cochez, Vrije Universiteit Amsterdam

Submissions and dates

Submissions can be in the form of:

• short papers: 4–6 pages;
• long papers: 9–12 pages.

All submission lengths are given including references. Accepted submissions will be published by ACL in an open-access conference proceedings volume, free of charge for authors. The ACL templates should therefore be used for all conference submissions . As the reviewing process is single-blind, submissions should not be anonymised.

The workshop will be hybrid. At least one author of each accepted paper is required to register for the workshop and present their work (either remotely or on-site). There will be no registration fee for participation.

Submissions must be submitted via EasyChair

Important dates:
Time Zone: Anywhere on Earth
Papers due: May, 19, 2023
Papers acceptance notifications: June, 16, 2023
Camera-ready papers due: June, 30, 2023
Registration for participation without submissions deadline: August 30th, 2023

Program committee

Andrius Utka, Vytautas Magnus University, Lithuania
Chaya Liebeskind, Jerusalem College of Technology, Israel
Ciprian-Octavian Truica, Uppsala University, Sweden
Cosimo Palma, University of Naples “L’Orientale” – University of Pisa, Italy
Dagmar Gromann, University of Vienna, Austria
Enriketa Sogutlu, University College Bedër, Albania
Giedre Valunaite Oleskeviciene, Mykolas Romeris University, Lithuania
Hugo Gonçalo Oliveira, University of Coimbra, Portugal
Jorge Gracia del Río University of Zaragoza, Spain
Mariana Damova, Mozaika, Bulgaria
Michael Cochez, Vrije Universiteit Amsterdam, Netherlands
Purificação Silvano, University of Porto, Portugal
Radovan Garabík, Ľ. Štúr Institute of Linguistics, Slovak Academy of Sciences, Slovakia
Sigita Rackevičienė, Mykolas Romeris University, Lithuania

Organizing committee

Giedrė Valūnaitė Oleškevičienė, Mykolas Romeris University, Lithuania
Radovan Garabík, Ľ. Štúr Institute of Linguistics, Slovak Academy of Sciences, Slovakia
Chaya Liebeskind, Jerusalem College of Technology, Israel
Cosimo Palma, University of Naples “L’Orientale” – University of Pisa, Italy
Enriketa Sogutlu, University College Bedër, Albania
Purificação Silvano, University of Porto, Portugal
Sigita Rackevičienė, Mykolas Romeris University, Lithuania

Contact:
gvalunaite@mruni.eu


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