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The Joint 15th Linguistic Annotation Workshop (LAW) and |
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Co-located with EMNLP 2021 – November 11, 2021 |
Linguistic annotation of natural language corpora is the backbone of supervised methods of statistical natural language processing and has contributed to breakthroughs in practical natural language applications, most notably in Machine Translation, Machine Reading, Question Answering, and Recognizing Textual Entailment. Nonetheless, challenges remain in developing systems that can actually ``understand'' human language, including the ability to track entities in a text, understand the relations between these entities, track events and their participants described in a text, understand how events unfold in time, and distinguish events that have actually happened from events that are planned or intended, are uncertain, or did not happen at all. The fifteenth LAW and third DMR workshops are combined for the first time to provide a forum for presentation and discussion of innovative research on all aspects of linguistic annotation, with a special focus on the design and annotation of representations of the various elements of meaning contributing to natural language understanding.
This workshop intends to bring together researchers who are producers and consumers of linguistic annotations and meaning representations. Through their interaction, we will gain a deeper understanding of both the kinds of annotations generally, and the key elements of meaning representations specifically, that are the most valuable to the NLP community. The workshop will also provide an opportunity for researchers to critically examine existing annotation frameworks and to explore opportunities and identify challenges in the design and use of linguistic annotations in multilingual settings.
Given that this is the first joint LAW and DMR workshop, a final goal of this workshop will be to explore multi-layered annotations and how different types of annotations can be brought together to enhance progress towards true understanding. This may include annotation schemas representing multiple facets of meaning (for example, both semantic roles and coreference), or leveraging one type of annotation to bootstrap obtaining another (for example, leveraging automatic SRL for a sentential meaning representation). This may also include annotations from multiple modalities (for example, transcribed text and accompanying images), as understanding can often hinge upon linguistic meaning within a particular situated context.
Submissions should report original and unpublished research on topics of interest to the workshop. Accepted papers are expected to be presented at the workshop and will be published in the workshop proceedings. They should emphasize obtained results rather than intended work, and should indicate clearly the state of completion of the reported results.
A paper accepted for presentation at the workshop must not be or have been presented at any other meeting with publicly available proceedings.
Long papers may consist of up to eight (8) pages of content, plus unlimited references, short papers may consist of up to four (4) pages of content; final versions will be given one additional page of content so that reviewers' comments can be taken into account. Submissions should be sent in electronic forms, using the Softconf START conference management system: https://www.softconf.com/emnlp2021/LAW-DMR/
We invite original research papers from a wide range of topics, including but not limited to:
Submissions are open to all, and are to be submitted anonymously. All papers will be refereed through a double-blind peer review process by at least three reviewers with final acceptance decisions made by the workshop organizers.
Both long and short papers must follow the EMNLP 2021 two-column format, using the supplied official style files. Please do not modify these style files, nor should you use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be rejected without review.
Instructions For Double-Blind Review As reviewing will be double blind, papers must not include authors’ names and affiliations. Furthermore, self-references or links (such as github) that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …” must be avoided. Instead, use citations such as “Smith previously showed (Smith, 1991) …” Papers that do not conform to these requirements will be rejected without review. Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above (“Smith showed” rather than “we showed”). If important citations are not available to reviewers (e.g., awaiting publication), these paper/s should be anonymised and included in the appendix. They can then be referenced from the submission without compromising anonymity. Papers may be accompanied by a resource ( software and/or data) described in the paper, but these resources should also be anonymized.
Dual submissions are allowed. Authors of papers that have been or will be submitted to other meetings or publications must provide this information to the workshop co-chairs (law-dmr-2021-chairs@googlegroups.com). In your message, please list the names and dates of the conferences, workshops or meetings where you have submitted or plan to submit your paper in addition to LAW. Authors of accepted papers must notify the program chairs within 10 days of acceptance if the paper is withdrawn for any reason.
If you have any questions, please feel free to contact the program co-chairs.