Triple

T14352356
Position Surface form Disambiguated ID Type / Status
Subject Dantokpa Market E355885 entity
Predicate languageOfName P15 FINISHED
Object Fon E171113 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: Fon | Statement: [Dantokpa Market, languageOfName, Fon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fon
Context triple: [Dantokpa Market, languageOfName, 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. Fung
    Fung is a common Cantonese romanization of the Chinese surname typically spelled "Feng" in Mandarin pinyin.
  • D. FUNO
    FUNO is the stock ticker symbol for Fibra Uno, one of Mexico’s largest real estate investment trusts (REITs) focused on commercial properties.
  • E. Fono
    The Fono is the bicameral legislative body of American Samoa, responsible for making territorial laws and overseeing local governance.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f4ff1e48190bd9419d70098cede completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4335e481909d4db39b8d25edc9 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:14 a.m.