AIDA Scenario 1 Practice Topic Annotation

Item Name: AIDA Scenario 1 Practice Topic Annotation
Author(s): Jennifer Tracey, Stephanie Strassel, Jeremy Getman, Ann Bies, Kira Griffitt, David Graff, Christopher Caruso
LDC Catalog No.: LDC2024T02
ISLRN: 462-429-870-532-3
DOI: https://doi.org/10.35111/ffya-kx44
Release Date: February 15, 2024
Member Year(s): 2024
DCMI Type(s): Text
Data Source(s): discussion forum, newswire, web collection, weblogs
Project(s): AIDA
Application(s): entity extraction, information extraction
Language(s): English, Russian, Ukrainian
Language ID(s): eng, rus, ukr
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2024T02 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Tracey, Jennifer, et al. AIDA Scenario 1 Practice Topic Annotation LDC2024T02. Web Download. Philadelphia: Linguistic Data Consortium, 2024.
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Introduction

AIDA Scenario 1 Practice Topic Annotation was developed by the Linguistic Data Consortium (LDC) and is comprised of annotations for 212 English, Russian and Ukrainian web documents (text, image and video) from AIDA Scenario 1 Practice Topic Source Data (LDC2023T11).

The DARPA AIDA (Active Interpretation of Disparate Alternatives) program aimed to develop a multi-hypothesis semantic engine to generate explicit alternative interpretations of events, situations and trends from a variety of unstructured sources. LDC supported AIDA by collecting, creating and annotating multimodal linguistic resources in multiple languages.

Each phase of the AIDA program centered on a specific scenario, or broad topic area, with related subtopics designated as either practice subtopics or evaluation subtopics. The Phase 1 scenario focused on political relations between Russia and Ukraine in the 2010s. This corpus contains annotations for the set of practice documents designated for annotation in Phase 1.

Data

Annotations are presented as tab separated files in the following categories for each topic.

  • Mentions: single references in source data to a real-world entity or filler, event, or relation. There are three mentions tables for each topic, one for entities and fillers, one for relations, and one for events.
  • Slots: pre-defined roles in an event or relation filled by an argument (entity mention). There are two slots tables per topic, one for relations and one for events.
  • Linking: entity mentions "linked" to entries in the knowledge base as a method of indicating the real-world entity to which an entity referred.

Sponsorship

This material is based upon work supported by Air Force Research Laboratory (AFRL) and the Defense Advanced Research Projects Agency (DARPA) under Contract No. FA8750-18-C-0013.

Samples

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Updates

None at this time.

 

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