Call for papers
The 6th edition of BSNLP workshop will be sponsored by SIGSLAV: the ACL Special Interest Group on Slavic NLP.THEME and MOTIVATION
Languages from the Balto-Slavic group play an important role due to their diverse cultural heritage and widespread use -- with over 400 million speakers worldwide. The recent political and economic developments in Central and Eastern Europe have brought Balto-Slavic societies and their languages into focus in terms of rapid technological advancement and rapidly expanding consumer markets.
This Workshop addresses Natural Language Processing (NLP) for the Balto-Slavic languages. The NLP tasks in urgent need of attention include, but are not limited to:
- morphological analysis and generation,
- morphosyntactic tagging,
- syntactic and semantic parsing,
- lexical semantics,
- named-entity recognition,
- text normalisation and processing non-standard language
- coreference resolution,
- information extraction,
- question answering,
- information retrieval,
- text summarization,
- machine translation,
- development of linguistic resources.
Research on theoretical and applied topics in the context of some of the Balto-Slavic languages is still in its early stages. The linguistic phenomena specific to Balto-Slavic languages -- such as rich morphological inflection and free word order -- make the construction of NLP tools for these languages a challenging and intriguing task.
The goal of this Workshop is to bring together researchers from academia and industry working on NLP for Balto-Slavic languages. In particular, the Workshop will serve to stimulate the research on NLP techniques for Balto-Slavic languages, and to foster the creation of tools and resources for these languages. The Workshop will provide a forum for exchanging ideas and experience, discussing difficult-to-tackle problems, and making the resources that are available more widely-known. One fascinating aspect of this sub-family of languages is the striking structural similarity, as well as an easily recognizable core vocabulary and inflectional inventory spanning the entire group of languages -- despite a lack of mutual intelligibility -- which creates a special environment in which researchers can fully appreciate the shared problems and solutions and communicate naturally. This Workshop continues the proud tradition established by the previous BSNLP Workshops.
SUBMISSION:
There will be two types of submissions: long papers and short papers.
Long papers should describe original, unpublished and completed work. Short papers should describe: (a) work in progress and/or small focused contributions, or (b) system demonstrations, new linguistic resources and experience of using existing software and resources, or (c) ongoing projects and activities that are relevant to all stakeholders in the domain of Balto-Slavic NLP.
Overlap with previously published work should be clearly mentioned. The authors should indicate along with their submission if the paper has been submitted elsewhere, e.g., to the main conference. In particular, in case the paper is rejected by the main conference, it should be indicated in the submission.
All submissions will be judged on correctness, novelty, technical strength, clarity of presentation, usability, and significance/relevance to the Workshop. Submissions will be reviewed by at least three members of the Program Committee.
The reviewing of long papers will be blind. Therefore, long papers should not include the authors' names and affiliations. Self-citations and other references that reveal the authors' identity must be avoided.
The short papers could be anonymized but this is not necessary.
In particular, submissions describing systems, resources, or solutions that are made available to the wider public would be strongly encouraged, as this would help to promote computational linguistics applications for Balto-Slavic languages.
Long paper submissions should follow the two-column format of EACL 2017 proceedings not exceeding eight (8) pages of content plus two (2) additional pages for references. Short paper submissions should follow the same format, and should not exceed four (4) pages for content plus two (2) additional pages for references. Submissions must conform to the official style guidelines of EACL 2017, which are contained in the style files, and must be in PDF. Camera-ready versions of accepted papers must be provided both in LaTeX and PDF format.
PROGRAMME
The workshop will consists of:
- oral presentations of accepted long and selected short papers,
- two invited talks by prominent researchers in Balto-Slavic NLP,
- session dedicated to the shared task, including presentation of participants’ solutions (see below), and
- interactive session for presenting selected short papers that describe systems, resources and projects that will start with a two-minute pitch-style introduction of each of the papers
We are currently in the process of exploring with the Programme Committee the selection of the most appropriate keynote speaker(s) for the workshop.
SHARED TASK
For the first time at BSNLP, we are envisioning a shared task on Named Entity Recognition and lemmatization in heterogeneous and multilingual collections of Web documents in Slavic languages. The Joint Research Centre of the European Commission will provide a corpus consisting of sets of links to web documents, where each such set covers Web documents that are related to one specific entity and contains information in several Slavic languages. The participants will be tasked to test their multilingual techniques for named entity recognition and named entity lemmatization, the latter generally being particularly difficult for Slavic languages due to rich inflection, free word order, derivation and other phenomena. This area is highly relevant for the development of Entity Linking, which in turn enables multilingual and cross-lingual information access, semantic processing based on knowledge graphs, etc.
The participants of the shared task will be invited to submit the description of their solutions and experience as short papers.
More information about shared task