SECOND CALL FOR ABSTRACTS
We would like to invite the submission of abstracts for the
computational linguistics poster session of the 45th annual meeting of
the German Linguistic Society (DGfS) hosted by the University of
Cologne. Since the meeting brings together numerous subfields of
linguistics, this is an opportunity to share your work with colleagues
both in and out of the computational linguistics field. We invite
submissions from all areas of computational linguistics and natural
language processing, ranging from machine translation and information
retrieval to speech and dialogue systems and cognitive modeling. We
especially encourage students and junior researchers to participate.
The poster session is organized by the Special Interest Group on
Computational Linguistics of the DGfS (dgfs.de/cl).
Conference homepage: https://dgfs2023.uni-koeln.de/
DATES
- Abstract submission due: October 28, 2022
- Notification of acceptance: November 4, 2022
- Short abstract (for conference website/brochure) due: November 18, 2022
- Conference dates: March 8-10, 2023
SUBMISSION
One page abstract (A4) in PDF format (12pt). Submissions can be in
German or English.
Please submit your abstract via email to: rainer.osswald(a)hhu.de
--
Dr. Rainer Osswald
Department of Computational Linguistics
Heinrich-Heine-Universität Düsseldorf
Universitätsstraße 1
40225 Düsseldorf, Germany
https://user.phil.hhu.de/osswald/
Dear colleagues,
we are writing to inform you that the abstract submission deadline for the
23rd AItLA conference has been extended until *November 3rd*.
The conference topic will be *Multimodal communication: contexts,
practices, resources*.
Confirmed invited speakers include Simona Pekarek Doehler (Université de
Neuchâtel) and Henk van den Heuvel (Radboud Universiteit).
Please, find the call for papers and all relevant information here
<http://www.aitla.it/10-primopiano/816-xxiii-congresso-internazionale-aitla-…>
Feel free to share the call with your networks.
Best,
Letizia Cirillo
(on behalf of the organizing committee)
In this newsletter:
Membership Year 2023 publication preview
LDC data and commercial technology development
30th Anniversary Highlight: ACE
New publications:
Rime-Cantonese: A Normalized Cantonese Jyutping Lexicon<https://catalog.ldc.upenn.edu/LDC2022L01>
2017 NIST Language Recognition Evaluation Training and Development Sets<https://catalog.ldc.upenn.edu/LDC2022S10>
LORELEI Bengali Representative Language Pack<https://catalog.ldc.upenn.edu/LDC2022T05>
________________________________
Membership Year 2023 publication preview
The 2023 membership year is approaching and plans for next year’s publications are in progress. Among the expected releases are:
* AIDA Ukrainian Broadcast and Telephone Speech Audio and Transcripts: 156 hours of Ukrainian conversational telephone speech and broadcast news with 1.2 million words of corresponding orthographic transcripts
* 2019 NIST SRE: audiovisual and leaderboard challenge sets based on amateur videos and Tunisian Arabic telephone speech, respectively
* DEFT English ERE: English text from assorted genres annotated for entities, relations, and events
* Mixer 3 and Mixer 7 speech collections: thousands of hours of telephone speech and metadata from Mixer 3 (multiple languages) and Mixer 7 (Spanish, plus interviews and transcript readings)
* CALLFRIEND Russian: 100 telephone conversations among native speakers, transcripts, and a lexicon, released in separate speech and text data sets
* REMIX Telephone Collection: English telephone speech from 385 participants in previous Mixer studies
* LORELEI: representative and incident language packs containing monolingual text, bi-text, translations, annotations, supplemental resources, and related tools in various languages (e.g., Indonesian, Swahili, Tagalog, Tamil, Zulu)
Check your inbox in the coming weeks for more information about membership renewal.
LDC data and commercial technology development
For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing<https://www.ldc.upenn.edu/data-management/using/licensing> page for further information.
30th Anniversary Highlight: ACE
The objective of the Automatic Content Extraction (ACE) program was to develop the capability to extract meaning (entities, relations and events) from multimedia sources (Doddington, et al., 2004<https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/lrec2004-ace-progra…>). LDC supported ACE by creating annotation guidelines, corpora and other linguistic resources, including training and test data for the common task research evaluations (Strassel, et al., 2003<https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/acl2003-multilingua…>; Huang, et al., 2004<https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/ijcnlp2004-shared-r…>).
There are multiple data sets in LDC’s Catalog from the program. One that regularly makes the list of LDC’s top ten most licensed corpora is ACE 2005 Multilingual Training Corpus (LDC2006T06<https://catalog.ldc.upenn.edu/LDC2006T06>). This data set contains 1,800 files of mixed genre text in English, Arabic, and Chinese annotated for entities, relations, and events. The genres include newswire, broadcast news, broadcast conversation, weblog, discussion forums, and conversational telephone speech.
Another popular data set, ACE 2004 Multilingual Training Corpus (LDC2005T09<https://catalog.ldc.upenn.edu/LDC2005T09>), consists of varied genre text in English (158,000 words), Chinese (307,000 characters, 154,000 words), and Arabic (151,000 words) annotated for entities and relations.
ACE 2007 Multilingual Training Corpus (LDC2014T18<https://catalog.ldc.upenn.edu/LDC2014T18>) has the complete set of Arabic and Spanish training data for the 2007 ACE technology evaluation, specifically, Arabic and Spanish newswire data and Arabic weblogs annotated for entities and temporal expressions.
Other ACE corpora in the Catalog include ACE 2005 SpatialML Annotations in English and Mandarin (LDC2008T03<https://catalog.ldc.upenn.edu/LDC2008T03>, LDC2010T09<https://catalog.ldc.upenn.edu/LDC2010T09>, and LDC2011T02<https://catalog.ldc.upenn.edu/LDC2011T02>), Datasets for Generic Relation Extraction (reACE)<https://catalog.ldc.upenn.edu/LDC2011T08>, TIDES Extraction (ACE) 2003 Multilingual Training Data<https://catalog.ldc.upenn.edu/LDC2004T09>, ACE-2 Version 1.0<https://catalog.ldc.upenn.edu/LDC2003T11>, ACE Time Normalization (TERN) 2004 English Training Data v 1.0 (TERN)<https://catalog.ldc.upenn.edu/LDC2005T07>, and more.
For the full list of available ACE data, visit LDC’s Catalog<https://catalog.ldc.upenn.edu/search> and select the ACE research project in the search menu. For more information about linguistic resources for the ACE Program, including annotation guidelines, task definitions and other documentation, visit LDC's ACE webpage<https://www.ldc.upenn.edu/collaborations/past-projects/ace>.
________________________________
New publications:
Rime-Cantonese: A Normalized Cantonese Jyutping Lexicon<https://catalog.ldc.upenn.edu/LDC2022L01> was developed by the Cantonese Computational Linguistics Infrastructure Working Group. It contains approximately 130,000 Cantonese character, word, and phrase entries paired with their corresponding romanized pronunciations in Jyutping<https://jyutping.org/en/>, a scheme created by The Linguistic Society of Hong Kong.
Data was collected from a variety of physical and online sources. The character collection was subjected to a normalization process for differences between traditional and simplified Chinese, regional differences and other variants in Chinese characters, and differences in orthography.
2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.
*
2017 NIST Language Recognition Evaluation Training and Development Sets<https://catalog.ldc.upenn.edu/LDC2022S10> contains training and development material for the 2017 NIST Language Recognition Evaluation<https://www.nist.gov/itl/iad/mig/nist-2017-language-recognition-evaluation>. It consists of 2,100 hours of conversational telephone speech, broadcast conversation, broadcast narrow band speech, and speech from video in the following 14 languages, dialects, and varieties: Arabic (Iraqi, Levantine, Maghrebi, Egyptian), English (British, American), Polish, Russian, Portuguese (Brazilian), Spanish (Caribbean, European, Latin American Continental), and Chinese (Mandarin, Min Nan). The 2017 evaluation focused on differentiating closely related language pairs. Source data is from LDC's CALLFRIEND and Fisher telephone collections, the VAST video collection, various broadcast sources, and earlier NIST LRE test sets.
2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.
*
LORELEI Bengali Representative Language Pack<https://catalog.ldc.upenn.edu/LDC2022T05> was developed by LDC and is comprised of approximately 144 million words of Bengali monolingual text, 96,000 Bengali words translated from English data, and over 2 million words of found Bengali-English parallel text. Approximately 86,000 words were annotated for named entities and up to 25,000 words were annotated for entity discovery and linking and situation frames (identifying entities, needs and issues). Data was collected from news, social network, and weblogs.
The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations. Representative languages were selected to provide broad typological coverage.
The knowledge base for entity linking annotation is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10)<https://catalog.ldc.upenn.edu/LDC2020T10>.
2022 members can access this corpus through their LDC accounts. Non-members may license this data for a fee.
To unsubscribe from this newsletter, log in to your LDC account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to “Receive Newsletter” under Account Options; or contact LDC for assistance.
Membership Coordinator
Linguistic Data Consortium<ldc.upenn.edu>
University of Pennsylvania
T: +1-215-573-1275
E: ldc(a)ldc.upenn.edu<mailto:ldc@ldc.upenn.edu>
M: 3600 Market St. Suite 810
Philadelphia, PA 19104
Position as Senior Researcher in Interactive Conversational Systems at DFKI Saarbrücken, Germany
# More Information and Hiring System available here: https://jobs.dfki.de/en/vacancy/en-senior-researcher-in-interactive-convers…
The MLT lab, led by Prof. Josef van Genabith, is looking for a senior researcher in Interactive Conversational Systems and Dialog Systems, to lead the Talking Robots Group (https://www.dfki.de/en/web/research/research-departments/multilinguality-an…)<Position%20as%20Senior%20Researcher%20in%20Interactive%20Conversational%20Systems%20at%20DFKI%20Saarbru?cken,%20Germany> at DFKI in Saarbrücken, Germany. The Talking Robots group currently has 5 members of staff and engages in national and international research and development projects on robot-assisted disaster response, multilingual dialogue, human-robot interaction and more.
The successful applicant will:
- lead and develop the Talking Robots group scientifically
- coordinate basic research as well as industry-focused project acquisition
- lead projects to successful completion
- publish research results at top-tier NLP/HRI/ML conferences
- engage in PhD research supervision as well as teaching graduate modules (max. one per term)
- closely engage with the Machine Translation, Question Answering and Information Extraction and the Data and Resources groups at MLT.
Profile: ideal candidates have
- a PhD in Interactive Conversational/Dialog Systems, Speech and Multimodal Technologies, Machine Learning, Human Robot Interaction (HRI), Natural Language Processing (NLP), or Computer Science
- a strong track record in research and publication at top-tier NLP/HRI/ML conferences (ACL, EMNLP, HRI, AAAI, ICML, ICASSP, INTERSPEECH etc.)
- a strong track record in the acquisition and management of research and development projects
excellent English (oral and written). German a plus, but not a requirement.
We offer excellent working and research conditions with interesting research topics in an interdisciplinary team at an internationally renowned research institute. What you can expect:
- The opportunity to shape and drive research in Interactive Conversational Systems and the Talking Robots group
- Innovative projects and industry collaborations in language technology and AI
- An innovative and professional working environment
- While the initial contract is fixed term, permanent contracts are possible for successful team leads upon completion of the fixed term contract
For more information about our MLT lab please also visit: https://www.dfki.de/web/forschung/forschungsbereiche/sprachtechnologie-und-…
The position is 3 years fixed term initially. A permanent position is possible subsequently. The successful applicant is expected to start at DFKI during the first quarter of 2023.
To apply, please upload a short motivation letter, CV, list of publications and projects, as well as contacts for two references in our hiring system. The deadline for the receipt of an application is Nov 15, 2022. For informal questions, please contact simon.ostermann(a)dfki.de<mailto:simon.ostermann@dfki.de> .
The German Research Center for Artificial Intelligence (DFKI) is Germany's leading business-oriented research institution in the field of innovative software technologies based on artificial intelligence methods. In the international scientific community, DFKI ranks among the most recognized "Centers of Excellence" and currently is the biggest research center worldwide in the area of Artificial Intelligence and its application in terms of number of employees and the volume of external funds. The DFKI cooperates closely with national and international companies.
DFKI encourages applications from people with disability; DFKI intends to increase the proportion of female employees in the field of science and encourages women to apply for this position.
---
Dr. Simon Ostermann
Lab Manager | Senior Researcher
Multilinguality and Language Technology Lab
DFKI, Saarbrücken
Phone: +49 681 85775 5310
Web: https://simonost.github.io/home/ | http://www.dfki.de/mlt/
Campus Building D 3.1, Room 1.28
Stuhlsatzenhausweg 3
D-66123 Saarbrücken, Germany
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Deutsches Forschungszentrum für Künstliche Intelligenz GmbH
Firmensitz: Trippstadter Strasse 122, D-67663 Kaiserslautern
Geschäftsführung: Prof. Dr. Antonio Krüger (Vorsitzender), Helmut Ditzer | Vorsitzender des Aufsichtsrats: Dr.-Ing. Gabriël Clemens | Amtsgericht Kaiserslautern, HRB 2313
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Dear All,
we’re very pleased to confirm that the 2023 SCLA conference will take place in June 20123 and we hereby issue the full call for papers, see below.
With greetings to all and heartfelt thanks to Steven Clancy for serving as the local organizer,
Mirjam & Mateusz
Slavic Cognitive Linguistics Conference (SCLC-2023): first announcement and call for papers
The Slavic Cognitive Linguistics Association (SCLA; https://slavic.fas.harvard.edu/scla) will hold its 18th conference on June 1 – 3, 2023 at Harvard University. The conference will be locally organized and hosted by Steven Clancy and will be held in an on-site format.
Confirmed keynote speakers at SCLC-2023
Valentina Apresjan, HSE University, Moscow
Neil Bermel, University of Sheffield
Catherine Caldwell-Harris, Boston University
Call for papers
We invite abstracts for 20+10 minute presentations on any topic of relevance to Slavic Cognitive Linguistics. Abstracts should be based on work that has not yet been published. We especially encourage submissions from young researchers. Abstracts can be written in English or in any Slavic language and should not be longer than 500 words, including references. Each individual may be involved in a maximum of two abstracts (maximum one as sole author or as the first author). Abstracts will be evaluated anonymously so please refrain from any self-identification in the body of the abstract.
The deadline for abstract submission is January 15, 2023.
Abstracts should be submitted via google forms. Please follow this link:
https://forms.gle/nU7NaJboEKxyNc6L8
We also invite proposals for 2-3 practically oriented workshops on topics of interest to the SCLA community. The ideas for such workshops should be submitted to the organizers (fried(a)ff.cuni.cz<mailto:fried@ff.cuni.cz>) by January 15, 2023.
Authors will be notified of acceptance / rejection by February 10, 2023.
Conference website:
https://slavic.fas.harvard.edu/2023-conference
Conference fees:
Regular $80
Student (incl. PhD students) $50
Important dates
January 15, 2023: abstract submission deadline
February 10, 2023: notification of acceptance / rejection
March 31, 2023 : early bird registration deadline
May 15, 2023: final payment deadline for registration fees
June 1-3, 2023: SCLA conference
Travel & Accommodation
We will provide detailed travel and accommodation information later.
Organizing Committee
Mirjam Fried (Charles University, Prague, Czech Republic)
Mateusz-Milan Stanojević (University of Zagreb, Chroatia)
Steven Clancy (Harvard University, USA)
If you have any questions concerning SCLC-2023 (don’t hesitate to contact the local organizer, Steven Clancy, at sclancy(a)fas.harvard.edu<mailto:sclancy@fas.harvard.edu>
PHD STUDENTSHIPS IN COMPUTATIONAL LINGUISTICS, SPEECH TECHNOLOGY AND
COGNITIVE SCIENCE
Institute for Language, Cognition and Computation
School of Informatics
University of Edinburgh
The Institute for Language, Cognition and Computation (ILCC) at the
University of Edinburgh invites applications for three-year PhD
studentships starting in September 2023. ILCC is dedicated to the
pursuit of basic and applied research on computational approaches to
language, communication and cognition.
Primary research areas include:
* Natural language processing and computational linguistics
* Machine Translation
* Speech technology
* Dialogue, multimodal interaction, language and vision
* Computational Cognitive Science , including language and speech,
decision-making, learning and generalization
* Social Media and Computational Social Science
* Human-Computer interaction, design informatics, assistive and
educational technology
* Information retrieval and visualization
Approximately 10 studentships from a variety of sources are available,
covering both maintenance at the research council rate of GBP 16,062
(2022/23 rates) per year and tuition fees. Awards increase every year, typically
with inflation. Studentships are available for UK, EU, and non-EU nationals.
Applicants should have a strong undergraduate degree or equivalent in
computer science, cognitive science, AI, or a related discipline.
For a list of academic staff at ILCC with research areas, and for a
list of indicative PhD topics, please consult:
http://web.inf.ed.ac.uk/ilcc/people/academic-senior-research-staffhttp://www.ilcc.inf.ed.ac.uk/study/possible-phd-topics-in-ilcc
Details regarding the PhD programme and the application procedure can be found at:
http://www.ed.ac.uk/informatics/postgraduate/research-degrees/phd
There are TWO DEADLINES for applications to receive full consideration:
round 1: 25th November 2022
round 2: 27th January 2023
We strongly recommend that non-UK applicants submit their applications in
round 1, to maximise their chances of funding. Please direct inquiries to
the PhD admissions team at ilcc-admissions(a)inf.ed.ac.uk.
Please note that the 3-year ILCC PhD program is distinct from the UKRI
Centre for Doctoral Training in Natural Language Processing, which
offers a 4-year PhD with integrated study:
http://nlp-cdt.ac.uk/
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
Postdoc position at IRIT, Toulouse (France) – ANR AnDiAMO
Developing systems towards robust discourse parsing and its application
https://pagesperso.irit.fr/~Chloe.Braud/andiamo/
* Contract duration: 12 months (flexible)
* Starting date: December 2022 (flexible)
* Location: IRIT, Université P. Sabatier (Toulouse III)
* Remuneration: starting at 2,745 euros, gross salary, depending on experience
* Application deadline: the position will be open until fulfilled
* Send application by email to chloe.braud(a)irit.fr
Application procedure: please send a CV and a short letter motivating your application by detailing the following elements:
* indicate your **skills in machine learning**, e.g. the type of tasks you already worked on, the type of algorithms, the libraries used. Please specify your experience with neural architectures and pre-trained language models.
* describe your **interest and/or experience in natural language processing**, i.e. the type of tasks you already tried to solve if any, or similar problems you worked on, or why you now want to work in NLP and why you think your experience in another domain could be relevant
* If you are interested but don’t have a phd, rather a master / engineer diploma and your CV fits the requirements, please send me an email with the same information as above
Incomplete application will not be considered. The AnDiAMO project:
Natural Language Processing (NLP) is a domain at the frontier of AI, computer science and linguistics, aiming at developing systems able to automatically analyze textual documents. Within NLP, discourse parsing is a crucial but challenging task: its goal is to produce structures describing the relationships (e.g. explanation, contrast...) between spans of text in full documents, allowing for making inference on their content. Developing high-performing and robust discourse parsers could help to improve downstream applications such as automatic summarization or translation, question-answering, chat bots, e.g. [1,2,3]. However, current performance are still low, mainly due to the lack of annotated data (see e.g. [4] on monologues, [5] on dialogues, [6,7] for the multilingual setting).
In order to develop robust discourse parsers within the AnDiAMO project, we want to explore multi-objective settings, where the goal is ultimately to perform a discourse analysis, but relying on another related objective such as performing well on another task (e.g. morphological, syntactic or temporal analysis), or an application (e.g. sentiment analysis or argument mining). We will also explore the issues of cross-language and cross framework learning.
The position is funded by the ANR AnDiAMO project, for which an engineer has already been hired, master interns will also be recruited. Collaborations are planned with researchers in Toulouse, Grenoble, Nancy and Munich. The hired person will be part of the MELODI team at IRIT, participating in team and project meetings, and co-authoring articles. Research plan:
The recruited candidate will work on one or several of the following topics, depending on its interests:
- Data representation: Discourse processing requires information from various levels of linguistics analysis. For now, existing studies do not make it clear what kind of information is important and needed, and some potentially relevant sources of information are ignored. We plan to explore this issue within a multi-task learning setting, where a system has to jointly learn different tasks. We will experiment on classification tasks (discourse relation, segmentation) and on full discourse parsing.
- Transferring to new languages, domains and modalities: Developing systems that perform well on domains or languages that are different from those used at training time is crucial, especially if the adaptation can be done in an unsupervised way. It is especially important for discourse, since annotation is very hard and time-consuming. We plan to experiment with cross-lingual embeddings and to explore multi-task learning, but trying to understand how to integrate additional linguistic information with only little annotated data for auxiliary tasks. We also want to investigate dialogues, for which only a few discourse parsers exist, and better understand how it differs from monologues.
- Extrinsic evaluation: We will investigate a few downstream applications that could benefit from discourse information, as a way to give an extrinsic evaluation. We will explore pipeline systems, varying the way we encode the discourse information as input of our end system. We will also explore transfer learning strategies, either via multi-task learning or representation learning. We plan to start with cognitive impairment detection (e.g. schizophrenia, Alzheimer) and argument mining. More applications will be considered, depending on the interest of the recruited postdoc.
It will be possible to investigate other paths of research, such as few-shot or unsupervised learning, depending on the interest of the recruited candidate.Profile
* PhD degree in computer science or computational linguistics
* Good knowledge in Machine Learning is required
* Interest in language technology / NLP
* Good programming skills: preferably with Python, knowledge of PyTorch is a plus References
[1] Feng, X., Feng, X., Qin, B., and Geng, X. Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization. In Proceedings of IJCAI. 2019.
[2] Bawden, R., Sennrich, R., Birch, A., and Haddow, B. Evaluating Discourse Phenomena in Neural Machine Translation. In Proceedings of NAACL. 2018
[3] Xu, J., Gan, Z., Cheng, Y., & Liu, J. Discourse-Aware Neural Extractive Text Summarization. In Proceedings of ACL. 2020
[4] Koto, F., Lau, J. H., & Baldwin, T. Top-down Discourse Parsing via Sequence Labelling. In Proceedings of EACL. 2021
[5] Liu, Z., & Chen, N. Improving Multi-Party Dialogue Discourse Parsing via Domain Integration. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse. 2021
[6] Braud, C., Coavoux, M., & Søgaard, A. Cross-lingual RST Discourse Parsing. In Proceedings of EACL. 2017[7] Liu, Z., Shi, K., & Chen, N. DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse. 2021
Hi Adam,
the Alpino/LassySmall corpora for Dutch may have what you need, ie it
has manually verified annotation of shared conjuncts, also a bit more
general (ie including adjectival modifiers for instance) than what is
the rule for UD/EUD.
https://www.let.rug.nl/~vannoord/Lassy/
The data can be searched here: https://paqu.let.rug.nl:8068/
ie using the Xpath search function, //node[@rel="cnj"]/node[@index] for
Lassy Klein gives a good first impression of shared arguments,
best,
Gosse Bouma
>> Le 13 oct. 2022 à 09:06, Adam Przepiórkowski via Corpora <corpora(a)list.elra.info> a écrit :
>>
>> Dear All,
>>
>> I am looking for treebanks (of any kind; dependency, constituency, LFG, HPSG, …) with good – preferably manual – unambiguous annotation of coordinate structures, for any language.
>>
>> A typical UD treebank does not have a good annotation of coordinations, because vanilla UD does not distinguish between dependents of single conjuncts, as in I [came and [bought a book]], and shared dependents of conjuncts, as in I [[saw and bought] a book]. Enhanced UD can in principle make this distinction, but many EUD treebanks are automatically converted from vanilla UD treebanks, so this information is also often not available or not reliable. On the other hand, many constituency treebanks (including PTB) do not have explicit information about governors of coordinations (in I bought John and Mary interesting books the governor of John and Mary is bought and not, say, books), and – perhaps surprisingly – it is often not easy to guess the governor. So I am looking for treebanks that wear both kinds of information – about shared dependents and about governors – on their sleeves.
>>
>> Thanks, best,
>> Adam P.
>> _
--
Gosse Bouma, Communication and Information Science, Groningen University, P.o. box 716, 9700 AS Groningen
G.Bouma(a)rug.nl tel. +31-50-3635937
(with apologies for cross-posting)
UDW 23, WASHINGTON DC, MARCH 9-12, 2023
Universal Dependencies (UD) is a framework for cross-linguistically
consistent treebank annotation that has so far been applied to over 100
languages (https://universaldependencies.org). The framework is aiming to
capture similarities as well as idiosyncrasies among typologically
different languages.
The Universal Dependencies Workshop is a forum for discussion of the theory
and practice of UD, its use in research and development, and its future
goals and challenges. The five workshops so far were held at NoDaLiDa in
Gothenburg (2017), at EMNLP in Brussels (2018), at SyntaxFest in Paris and
Online (2019 and 2021) and at COLING online (2020). The sixth workshop on
Universal Dependencies will take place during the week of March 9th-12th,
2023 in Washington D.C. on the campus of Georgetown University as part of
GURT 2023.
We invite papers on all topics relevant to UD, including but not limited to:
- Theoretical foundations and universal guidelines
- Linguistic analysis of specific languages and/or constructions
- Language typology and linguistic universals
- Treebank annotation, conversion and validation
- Word segmentation, morphological tagging and syntactic parsing
- Downstream applications in natural language processing
- Linguistic studies based on the UD data
Priority will be given to papers that adopt a cross-lingual perspective.
VENUE
The Georgetown University Round Table on Linguistics (GURT) is a
peer-reviewed annual linguistics conference held continuously since 1949 at
Georgetown University in Washington DC, with topics and co-located events
varying from year to year. Under an overarching theme of ‘Computational and
Corpus Linguistics’, GURT 2023 will feature four workshops focused on
computational and corpus approaches to syntax: UDW, Depling, TLT, and
CxGs+NLP. Talks will take place in plenary sessions to promote
cross-fertilization of ideas across subcommunities.
INVITED SPEAKER
Joakim Nivre (RISE)
IMPORTANT DATES
- November 15, 2022: submission deadline (long and short papers)
- January 11, 2023: notification of acceptance
- February 1, 2023: camera-ready papers due
- March 9–12, 2023: conference
SUBMISSION INFORMATIONS
We invite paper submissions in two distinct tracks:
- Regular papers on substantial, original, and unpublished research,
including empirical evaluation results, where appropriate
- Short papers on smaller, focused contributions, work in progress,
negative results, surveys, or opinion pieces.
All papers accepted for presentation at the workshop will be included in
the UDW23 proceedings volume, which will be part of the ACL Anthology.
See details at https://gurt.georgetown.edu/gurt-2023/udw-call-for-papers
Depending on the number of submissions, we will also accept a small number
of short, non-archival communications, mainly opinion pieces and discussion
on evolution to UD. Please contact the workshop chairs directly.
CONTACT:
Loïc Grobol (Université Paris Nanterre)
Francis Tyers (Indiana University)
Website: https://universaldependencies.org/udw23/
--
Loïc Grobol (they/them)
MCF / Assistant Professor
MoDyCo, Université Paris Nanterre
Academic webpage: https://loicgrobol.github.io