Triple

T9193433
Position Surface form Disambiguated ID Type / Status
Subject Forces Armées Nationales Tchadiennes E220644 entity
Predicate shortName P43 FINISHED
Object FANT
FANT is the acronym for Chad’s national armed forces, responsible for the country’s defense and military operations.
 E783229 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: FANT | Statement: [Forces Armées Nationales Tchadiennes, shortName, FANT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FANT
Context triple: [Forces Armées Nationales Tchadiennes, shortName, FANT]
  • A. FAN
    FAN is the French acronym for Niger's national military, responsible for the country's defense and security operations.
  • B. FANK
    FANK was the acronym for the Khmer National Armed Forces, the military of the pro-U.S. Lon Nol government in Cambodia during the Cambodian Civil War.
  • C. Fantswam
    Fantswam are a subgroup of the Atyap people, an ethnic community indigenous to southern Kaduna State in Nigeria with their own distinct cultural and linguistic identity.
  • D. FAB
    FAB is the acronym for the Brazilian Air Force, the aerial warfare branch of Brazil’s armed forces.
  • E. FAB
    FAB is the IATA airport code for Farnborough Airport, a business aviation airport in Hampshire, England.
  • 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: FANT
Triple: [Forces Armées Nationales Tchadiennes, shortName, FANT]
Generated description
FANT is the acronym for Chad’s national armed forces, responsible for the country’s defense and military operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FANT
Target entity description: FANT is the acronym for Chad’s national armed forces, responsible for the country’s defense and military operations.
  • A. FAN
    FAN is the French acronym for Niger's national military, responsible for the country's defense and security operations.
  • B. FANK
    FANK was the acronym for the Khmer National Armed Forces, the military of the pro-U.S. Lon Nol government in Cambodia during the Cambodian Civil War.
  • C. Fantswam
    Fantswam are a subgroup of the Atyap people, an ethnic community indigenous to southern Kaduna State in Nigeria with their own distinct cultural and linguistic identity.
  • D. FAB
    FAB is the acronym for the Brazilian Air Force, the aerial warfare branch of Brazil’s armed forces.
  • E. FAB
    FAB is the IATA airport code for Farnborough Airport, a business aviation airport in Hampshire, England.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5c1fa9c8190bc5cc6dce8778694 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c313004819090fe0e5d4e7bc15e completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d05d138c288190a0eab9be6bd649c0 completed April 4, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69d05df1a0888190a2bdc48a159b865e completed April 4, 2026, 12:40 a.m.
Created at: March 30, 2026, 7:24 p.m.