Triple

T9193480
Position Surface form Disambiguated ID Type / Status
Subject Forces Armées du Nord E220645 entity
Predicate shortName P43 FINISHED
Object FAN E783526 NE FINISHED

How this triple was built (2 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: FAN | Statement: [Forces Armées du Nord, shortName, FAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FAN
Context triple: [Forces Armées du Nord, shortName, FAN]
  • A. FAN
    FAN is the French acronym for Niger's national military, responsible for the country's defense and security operations.
  • B. FAN chosen
    FAN was a key rebel armed group in Chad that played a major role in the country’s internal conflicts during the late 20th century.
  • C. 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.
  • D. FANT
    FANT is the acronym for Chad’s national armed forces, responsible for the country’s defense and military operations.
  • E. FAN-nee
    FAN-nee is the stress pattern indicating that the primary emphasis falls on the first syllable of the name “Fannie.”
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d065d5e81c8190b6687999a87fd559 completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 7:25 p.m.