Second Call for Papers: The 20th Linguistic Annotation Workshop (LAW XX), co-located with ACL 2026, San Diego
Website: �https://sigann.github.io/LAW-XX-2026/ � Linguistic annotation of natural language corpora is the backbone of supervised methods in both statistical and neural natural language processing. Annotated corpora are also a major supporting source of information for unsupervised methods, multitask learning, and evaluation of both NLP tools and theories about language within and outside of linguistics. LAW-XX will provide a forum for presentation and discussion of innovative research on all aspects of linguistic annotation, including creation/evaluation of annotation schemes, methods for automatic and manual annotation, use and evaluation of annotation software and frameworks, representation of linguistic data and annotations, semi-supervised “human in the loop” methods of annotation, crowd-sourcing approaches, and more. LAW XX will also provide a forum for annotation researchers to work towards standardization, best practices, and interoperability of annotation information and software. � Special Theme: Errors in Annotation The special theme of LAW XX is �Errors in Annotation. In addition to LAW’s general topics, we specifically invite submissions on the matter of addressing annotations which are in some sense objectively incorrect in their substance or omissions (c.f. �Klie et al., CL 2023)—distinct from annotator disagreement (Weber-Genzel et al., ACL 2024)—and the role of error analysis in improving data quality for both human-annotated and LLM-generated datasets. As data quality becomes increasingly important (human-annotated or LLM-generated), it is essential to develop techniques or tools to quantify data quality (Swayamdipta et al., EMNLP 2020). � � Potential topics covered include but are not limited to: * Annotation error detection * Annotation error correction * Error type classification * Error detection and correction in crowd-sourced annotations * Errors in LLM-generated annotations � Important Dates All submission deadlines are 11:59 p.m. UTC-12:00 ("anywhere on Earth"). � * Submission deadline: March 5, 2026 * Pre-reviewed ARR commitment deadline: March 24, 2026 * Notification of acceptance: April 28, 2026 * Camera-ready papers due: May 12, 2026 * Workshop Date: TBD � LAW XX will be hybrid, allowing both in-person and virtual presentations. � Submission Information 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 o Innovative automated and manual strategies for annotation o Machine learning and knowledge-based methods for automation of corpus annotation o Creation, maintenance, and interactive exploration of annotation structures and annotated data * Annotation evaluation o Inter-annotator agreement and other evaluation metrics and strategies o Qualitative evaluation of linguistic representations o Innovative means to evaluate annotation quality * Annotation access and use o 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 o New and innovative annotation schemes, comparison of annotation schemes o Methodologies and resources for annotation scheme development o Best practices for annotation procedures and/or development and documentation of annotation schemes o 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 o Annotation software and frameworks o Development, evaluation and/or innovative use of annotation software frameworks � Direct submission �link: �https://openreview.net/group?id=aclweb.org/ACL/2026/Workshop/LAW Pre-reviewed ARR commitment �link: �https://openreview.net/group?id=aclweb.org/ACL/2026/Workshop/LAW_ARR_Commitment � Note on OpenReview's moderation policy for �newly created profiles: * New profiles created without an institutional email will go through a moderation process that �can take up to two weeks. * New profiles created with an institutional email will be activated automatically. � Submissions should report original and unpublished research on topics of interest to the workshop. We also invite substantiated position papers, in particular with regard to our special theme. Accepted papers are expected to be presented at the workshop (either in-person or virtually) 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/short paper submissions must use �the official ACL style templates. Long papers must not exceed eight (8) pages of content. Short papers and demonstration papers must not exceed four (4) pages of content. References do not count against these limits. Limitation and ethical consideration sections are optional and do not count against these limits as well. � Note: The appendix also does not count against the page limit but should not include essential details needed to understand/review the paper (appendices can contain details such as hyperparameters, formulas, proofs, and tables that are informative but not critical to the understanding of the paper). All submissions must be in PDF format. � Reviewing of papers will be double-blind. � � Authors of papers that have been or will be submitted to other meetings or publications must provide this information to the workshop program chairs ( <mailto:[email protected]> [email protected]). Authors of accepted papers must notify the program chairs within 10 days of acceptance if the paper is withdrawn for any reason. � Following �the ACL and ARR policies, there is no anonymity period requirement. �
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