Linguistic annotation of natural language corpora is the backbone of supervised methods for statistical natural language processing. It also provides valuable data for evaluation of both rule-based and supervised systems and can help formalize and study linguistic phenomena.

The LAW provides a forum for presentation and discussion of innovative research on all aspects of linguistic annotation, including creation and evaluation of annotation schemes, methods for automatic and manual annotation, use and evaluation of annotation software and frameworks, representation of linguistic data and annotations, etc.

LAW XI is the annual workshop for the ACL Special Interest Group on Annotation (SIGANN), in 2017 it is co-located with the EACL.
Call for Papers

We welcome submissions of long and short papers, posters, and demonstrations relating to the special theme or any aspect of linguistic annotation, including:

Annotation procedures
Innovative automated and manual strategies for annotation
Machine learning and knowledge-based methods for automation of corpus annotation
Creation, maintenance, and interactive exploration of annotation structures and annotated data
Annotation evaluation
Inter-annotator agreement and other evaluation metrics and strategies
Qualitative evaluation of linguistic representations
Innovative means to evaluate annotation quality
Annotation access and use
Representation formats/structures for annotations of different phenomena, especially annotations at multiple levels, and means to explore/manipulate them
Linguistic considerations for merging annotations of distinct phenomena
Annotation schemes, guidelines and standards
New and innovative annotation schemes, comparison of annotation schemes
Methodologies and resources for annotation scheme development
Best practices for annotation procedures and/or development and documentation of annotation schemes
Interoperability of annotation formats and/or frameworks among different systems as well as different tasks, frameworks, modalities, and languages
Results from the application and evaluation of standards for linguistic annotation
Annotation software and frameworks
Development, evaluation and/or innovative use of annotation software frameworks

We also invite proposals for a shared task to be hosted at LAW 2018. These should be submitted as short papers (up to 4 pages). The program will include a panel discussion of potential shared tasks.
Submissions and Reviewing

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.

The maximum length is eight (8) pages of content for long papers and four (4) pages of content for short papers, posters, and demonstrations. References do not count toward the page limit.

Reviewing of papers will be double-blind. Therefore, the paper must not include the authors' names and affiliations or self-references that reveal the authors’ identity--e.g., "We previously showed (Smith, 1991) ..." should be replaced with citations such as "Smith (1991) previously showed ...". Papers that do not conform to these requirements will be rejected without review.

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-xi-2017-chairs@googlegroups.com). Authors of accepted papers must notify the program chairs within 10 days of acceptance if the paper is withdrawn for any reason.

More precise intructions on submission, including style files and submission web site, will be posted later.
با جستجو در پایگاه داده‌های ویپاب، کارگاه‌های آموزشی مورد نظر خود را بیابید و یا به ثبت اطلاعات یک کارگاه آموزشی بپردازید.
 

This is an animated dialog which is useful for displaying information. The dialog window can be moved, resized and closed with the 'x' icon.

These items will be permanently deleted and cannot be recovered. Are you sure?