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TAC 2020 Workshop

Recognizing Ultra Fine-grained Entities (RUFES) 2020

Conducted by:
U.S. National Institute of Standards and Technology (NIST)

With support from:
U.S. Department of Defense


The goal of TAC-KBP is to extract mentions of pre-defined entity types from any language, and cluster together mentions of the same entity. Many real world applications in scenarios such as disaster relief and technical support require systems that recognize a wide variety of entity types (e.g., technical terms, lawsuits, disease, crisis, vehicles, food, biomedical entities) with limited training data for each type. The KBP2020 RUFES task (Recognizing Ultra Fine-grained EntitieS) challenges systems to recognize name, nominal, and pronominal mentions of entities in news articles, from a newly developed ontology with over 200 types that cover a variety of topics in the news. In addition, humans will provide "feedback" on system output, which can be used to improve each system.

Mailing List

The mailing list for the KBP 2020 RUFES task is tac-kbp@list.nist.gov. Participants may join the mailing list by joining the tac-kbp Google Group. Group members will receive messages that are sent to the group mailing list. Messages to the mailing list should be sent to tac-kbp@list.nist.gov. A Google account (not necessarily a Gmail account) is required to join the group. Participants without a Google account who wish to join the mailing list should send a message to tac-manager@nist.gov with the subject line "subscribe tac-kbp". Registering to participate in the track does not automatically add you to the mailing list. If you were previously subscribed to the mailing list, you do not have to re-subscribe (the mailing list is for anyone interested in KBP at TAC, and thus carries over from year to year).

Organizing Committee

    Heng Ji (Coordinator, University of Illinois at Urbana-Champaign, hengji@illinois.edu)
    Avi Sil (Coordinator, IBM Research AI, avi@us.ibm.com)
    Hoa Trang Dang (U.S. National Institute of Standards and Technology, hoa.dang@nist.gov)
    Shudong Huang (U.S. National Institute of Standards and Technology, shudong.huang@nist.gov)
    Joel Nothman (University of Sydney, joel@it.usyd.edu.au)
    Ian Soboroff (U.S. National Institute of Standards and Technology, ian.soboroff@nist.gov)

Scientific Board

    Mausam (Indian Institute of Technology Delhi)
    Isabelle Augenstein (University of Copenhagen)
    Elizabeth Boschee (Information Sciences Institute)
    Laura Dietz (University of New Hampshire)
    Radu Florian (IBM Research AI)
    Alan J. Goldschen (U.S. Department of Defense)
    Ralph Grishman (New York University)
    Hanna Hajishirzi (University of Washington)
    Ed Hovy (U.S. Department of Defense)
    Yunyao Li (IBM Reseach AI)
    Andrew McCallum (University of Massachusetts Amherst)
    Paul McNamee (Johns Hopkins University)
    Graham Neubig (Carnegie Mellon University)
    Boyan Onyshkevych (U.S. Department of Defense)
    Marius Pasca (Google)
    Siddharth Patwardhan (Apple)
    Dan Roth (University of Pennsylvania)
    Xiang Ren (University of Southern California)
    Satoshi Sekine (RIKEN Center for Advanced Intelligence)
    Sameer Singh (University of California Irvine)

NIST is an agency of the
U.S. Department of Commerce

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Last updated: Wednesday, 16-Sep-2020 09:16:58 EDT
Comments to: tac-web@nist.gov