2020 The 6th Workshop on Noisy User-generated Text (W-NUT)

Nov 11, 2020, Punta Cana, Dominican Republic (at EMNLP 2020)

The WNUT workshop focuses on Natural Language Processing applied to noisy user-generated text, such as that found in social media, online reviews, crowdsourced data, web forums, clinical records and language learner essays. The workshop hashtag is #wnut.

We are organizing a shared-task on entity and relation recognition over wet-lab protocols. Data will be released in April and evaluation will be in June 2020 (more information here; sign up for mailing list for future announcements).

We have best paper awards sponsored by Twitter this year.

Workshop Organizers

Invited Speakers

Call for Papers

We seek submissions of long and short papers on original and unpublished work (same page limit EMNLP main conference). 1-page abstracts on work-in-progress or work published elsewhere are also welcome and will *not* be included in the conference proceedings. All accepted submissions will be presented as posters. Additionally, selected submissions will be presented orally.

Topics of interest include but are not limited to:

All submissions should conform to EMNLP 2020 style guidelines. Long and short paper submissions must be anonymized. Abstract submissions should include author information (and where the work was published in a footnote on the front page, if applicable). Please submit your papers at the SoftConf link.

Double Submission Policy: Papers that have been or will be submitted to other meetings or publications must indicate at submission time. Authors of a paper accepted for presentation must notify the workshop organizers by the camera-ready deadline as to whether the paper will be presented or withdrawn. (Exception: 1-page abstracts can be work-in-progress or work published elsewhere.)

Important Dates

Shared task: Lab Protocols

Lab protocols specify steps in performing a lab procedure. They are noisy, dense, and domain-specific. Automatic or semi-automatic conversion of protocols into machine-readable format benefits biological research. In this task, system entries are invited for event recognition and relation extraction over these lab protocols. Note that these protocols are written by researchers and lab technicians worldwide, some of which may contain non-standard language or spelling errors. Here's a sample of the input data:

Details on the shared task are here.

Program Committee