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TAC 2020 Workshop
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Streaming Multimedia Knowledge Base Population (SM-KBP) 2020
Evaluation: August 2020 - January 2021
Workshop: February 22-23, 2021
Conducted by:
U.S. National Institute of Standards and Technology (NIST)
With support from:
U.S. Department of Defense
Background
In scenarios such as natural disasters or international conflicts,
analysts and the public are often confronted with a variety of
information coming through multiple media sources. There is a need for
technologies to analyze and extract knowledge from multimedia to
develop and maintain an understanding of events, situations, and
trends as they unfold around the world.
The goal of DARPA's Active Interpretation of Disparate Alternatives
(AIDA) Program is to develop a multi-hypothesis semantic engine that
generates explicit alternative interpretations of events, situations,
and trends from a variety of unstructured sources, for use in noisy,
conflicting, and potentially deceptive information environments. This
engine must be capable of mapping knowledge elements (KE)
automatically derived from multiple media sources into a common
semantic representation, aggregating information derived from those
sources, and generating and exploring multiple hypotheses about the
events, situations, and trends of interest.
The streaming multimedia KBP track evaluates the performance of
systems that have been developed in support of AIDA program goals.
Following a pilot at TAC/TRECVID 2018, the first SM-KBP evaluation was
run at TAC/TRECVID 2019. It is expected that the SM-KBP track will be
run for a total of three phases of evaluation:
- Phase 1 Evaluation: June-August 2019
- Phase 2 Evaluation: August 2020 - January 2021
- Phase 3 Evaluation early 2022
Task Overview
The SM-KBP track has three evaluation tasks:
- Task 1: Extract mentions of Knowledge Elements from a stream of
multimedia documents (including text, image, and video) and cluster together
mentions of the same KE in each document to produce a document-level
knowledge graph for each document.
- Task 2: Aggregate and link the document-level knowledge graphs
from Task 1 to construct a KB of the entire document stream without
access to the raw documents themselves
- Task 3: Generate hypotheses from a knowledge graph from Task 2,
such that each hypothesis represents a semantically coherent
interpretation of the document stream.
While tasks 2 and 3 and limited to teams that are part of
DARPA's AIDA program, Tasks 1 is also open to non-AIDA researchers who are
interested in multilingual multimedia information extraction.
Ontology: Teams will receive an "annotation" ontology that
defines the entities, relations, events, and event and relation
roles and arguments that must be extracted. The ontology contains
approximately 180 entity types, 150 event types, and 50 relation
types, including couarse-grained types (e.g., PER, Conflict.Attack,
Physical.LocatedNear) and more fine-grained types (e.g.,
PER.Combatant.Sniper, Conflict.Attack.FireArmAttack,
Physical.LocatedNear.Surround).
Documents: Task 1 systems will process a set of
approximately 2000 documents in English, Spanish, and Russian, and
output a document-level knowledge graph for each document. A document
may contain multiple document elements in multiple modalities (text,
image, video); therefore, cross-lingual and cross-modal entity,
relation, and event coreference are required. For each document,
systems must extract all mentions of entities, relations, and events
and identify all arguments and temporal information for each event and
relation.
Leaderboard: System output will be
scored by comparing against gold standard annotations for a subset of
the documents, and scores reported on a leaderboard. Two leaderboards will be set up for Task 1: A dry run leaderboard to
submit results on practice documents, and an evaluation leaderboard to
submit results on evaluation documents. Teams may submit to the dry
run leaderboard as many times as desired, but they may submit to the
evaluation leaderboard only a limited number of times. All Task 1 participants will
submit to the same leaderboards, and scores will be viewable by all
registered SM-KBP teams. However, while non-AIDA teams will be given
the evaluation documents and will submit system output for evaluation,
AIDA teams will not be given the evaluation documents, but must
instead submit system dockers that will be run by NIST for the
evaluation.
Schedule
TAC SM-KBP 2020 Schedule |
August 28-October 18 | Task 1 Dry Run Leaderboard active (AIDA dockers only) |
September 21-October 18, 2020 | Task 1 Evaluation Leaderboard active (AIDA dockers only) |
December 8, 2020 | Task 1 Evaluation Source Corpus available (all participants) |
February 3, 2021 | Deadline for short system descriptions |
February 3, 2021 | Deadline for workshop presentation proposals |
February 8, 2021 | Notification of acceptance of oral presentation proposals |
February 14, 2021 | Deadline for system reports (workshop notebook version) |
February 22-23, 2021 | Thirteenth TAC workshop (online) |
April 1, 2021 | Deadline for system reports (final proceedings version) |
April 2021 | Task 1 Evaluation Leaderboard re-opens (all participants) |
Mailing List
Join the sm-kbp group to subscribe yourself to the sm-kbp@list.nist.gov mailing list (if not already subscribed):
Registering to participate in a 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 SM-KBP, rather than specifically for SM-KBP
participants, and thus carries over from year to year).
Organizing Committee
Hoa Trang Dang (U.S. National Institute of Standards and Techonology)
George Awad (U.S. National Institute of Standards and Techonology)
Asad Butt (U.S. National Institute of Standards and Techonology)
Shahzad Rajput (U.S. National Institute of Standards and Techonology)
Jason Duncan (MITRE)
Boyan Onyshkevych (U.S. Department of Defense)
Stephanie Strassel (Linguistic Data Consortium)
Jennifer Tracey (Linguistic Data Consortium)
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