Triple

T22338312
Position Surface form Disambiguated ID Type / Status
Subject Hafia FC E552208 entity
Predicate nickname P55 FINISHED
Object Hafia FC NE NERFINISHED

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: Hafia FC | Statement: [Hafia FC, nickname, Hafia FC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hafia FC
Context triple: [Hafia FC, nickname, Hafia FC]
  • A. Hafia FC chosen
    Hafia FC is a historically successful Guinean football club best known for dominating African club competitions in the 1970s, including multiple continental titles.
  • B. Al Fayha FC
    Al Fayha FC is a professional football club from Al Majma'ah, Saudi Arabia, that competes in the country’s top-tier Saudi Pro League.
  • C. African Stars FC
    African Stars FC is a prominent Namibian football club based in Windhoek, known for competing in the country’s top-tier league and winning multiple national titles.
  • D. Kallon FC
    Kallon FC is a Sierra Leonean football club known for developing talented players, including future international striker Kei Kamara.
  • E. Ittihad FC
    Ittihad FC is a prominent Saudi Arabian football club based in Jeddah, known as one of the country's oldest and most successful teams.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e494eec81909c4d2d51f69499d9 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1578184f481908d4ec1737a8a72d4 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.