AIDA Scenario 2 Practice Topic Annotation

Item Name: AIDA Scenario 2 Practice Topic Annotation
Author(s): Jennifer Tracey, Stephanie Strassel, Jeremy Getman, Ann Bies, Kira Griffitt, David Graff, Christopher Caruso
LDC Catalog No.: LDC2024T06
ISLRN: 410-297-940-352-7
Release Date: June 17, 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, Spanish
Language ID(s): eng, rus, spa
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2024T06 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Tracey, Jennifer, et al. AIDA Scenario 2 Practice Topic Annotation LDC2024T06. Web Download. Philadelphia: Linguistic Data Consortium, 2024.
Related Works: View


AIDA Scenario 2 Practice Topic Annotation was developed by the Linguistic Data Consortium (LDC) and is comprised of annotations for 29 English, Russian and Spanish web documents (text, image and video) from AIDA Scenario 2 Practice Topic Source Data (LDC2024T04).

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 2 scenario focused on the socioeconomic and political crisis in Venezuela since 2010. This corpus contains annotations for the set of practice documents designated for annotation in Phase 2.


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.


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.


Please view the following samples:


None at this time.

Available Media

View Fees

Login for the applicable fee