Triple

T19309499
Position Surface form Disambiguated ID Type / Status
Subject Virgin Islands Territorial Emergency Management Agency E482927 entity
Predicate shortName P43 FINISHED
Object VITEMA
VITEMA is the emergency management agency responsible for coordinating disaster preparedness, response, and recovery efforts in the U.S. Virgin Islands.
E1369464 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: VITEMA | Statement: [Virgin Islands Territorial Emergency Management Agency, shortName, VITEMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VITEMA
Context triple: [Virgin Islands Territorial Emergency Management Agency, shortName, VITEMA]
  • A. VITA
    VITA is an industry trade association that develops and promotes open standards for embedded computing systems, particularly those based on the VMEbus architecture.
  • B. Vitarte
    Vitarte is a district of Lima, Peru, known for its industrial activity and dense urban population.
  • C. VIAM
    VIAM is the ICAO airport code for Ambala Air Force Station, a major Indian Air Force base located in Ambala, Haryana, India.
  • D. VEIM
    VEIM is the ICAO airport code for Imphal International Airport, the main air gateway to the Indian state of Manipur.
  • E. VIVAT
    VIVAT is a Dutch insurance and asset management company that was acquired by China’s Anbang Insurance Group as part of its international expansion.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VITEMA
Triple: [Virgin Islands Territorial Emergency Management Agency, shortName, VITEMA]
Generated description
VITEMA is the emergency management agency responsible for coordinating disaster preparedness, response, and recovery efforts in the U.S. Virgin Islands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: VITEMA
Target entity description: VITEMA is the emergency management agency responsible for coordinating disaster preparedness, response, and recovery efforts in the U.S. Virgin Islands.
  • A. VITA
    VITA is an industry trade association that develops and promotes open standards for embedded computing systems, particularly those based on the VMEbus architecture.
  • B. Vitarte
    Vitarte is a district of Lima, Peru, known for its industrial activity and dense urban population.
  • C. VIAM
    VIAM is the ICAO airport code for Ambala Air Force Station, a major Indian Air Force base located in Ambala, Haryana, India.
  • D. VEIM
    VEIM is the ICAO airport code for Imphal International Airport, the main air gateway to the Indian state of Manipur.
  • E. VIVAT
    VIVAT is a Dutch insurance and asset management company that was acquired by China’s Anbang Insurance Group as part of its international expansion.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604cc62e08190b5ba5dfc44efdc5c completed April 20, 2026, 10:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a07145da9f081908db403f7f832731d completed May 15, 2026, 12:41 p.m.
NEDg Description generation batch_6a0715514bac8190aafb36b96d4b167d completed May 15, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_6a07163cb15881908435e7d2fa68b06e completed May 15, 2026, 12:49 p.m.
Created at: April 10, 2026, 1:32 p.m.