Triple

T14717796
Position Surface form Disambiguated ID Type / Status
Subject ASFA Yennenga E345728 entity
Predicate confederation P3193 FINISHED
Object CAF E34397 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: CAF | Statement: [ASFA Yennenga, confederation, CAF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CAF
Context triple: [ASFA Yennenga, confederation, CAF]
  • A. CAF chosen
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • B. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • C. CAF
    CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
  • D. CAF
    CAF is the commonly used abbreviation for the Chief of Air Force, the professional head of an air force service.
  • E. CAF
    CAF is a multilateral development bank that finances sustainable development and regional integration projects across Latin America and the Caribbean.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb98688f48190b2b19ce7aa06a6db completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0935f088190b54f2e106532972a completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:29 a.m.