Triple

T20062275
Position Surface form Disambiguated ID Type / Status
Subject Mina E499507 entity
Predicate neighboringLanguageGroup P38997 FINISHED
Object Fon 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: Fon | Statement: [Mina, neighboringLanguageGroup, Fon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fon
Context triple: [Mina, neighboringLanguageGroup, Fon]
  • A. Fon chosen
    Fon is a major Gbe language of West Africa, primarily spoken by the Fon people in Benin and neighboring countries.
  • B. Funka
    Funka is a small village in northern Poland known for its scenic lakeside setting and recreational access to Lake Charzykowskie.
  • C. Funt
    Funt is a surname most notably associated with Allen Funt, the creator and host of the pioneering hidden-camera television show "Candid Camera."
  • D. Fung
    Fung is a common Cantonese romanization of the Chinese surname typically spelled "Feng" in Mandarin pinyin.
  • E. FUNO
    FUNO is the stock ticker symbol for Fibra Uno, one of Mexico’s largest real estate investment trusts (REITs) focused on commercial properties.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66376f2d4819081b9e1b265650e5b completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.