Triple

T7534329
Position Surface form Disambiguated ID Type / Status
Subject Ouidah E178108 entity
Predicate languageUsed P238 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: [Ouidah, languageUsed, Fon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fon
Context triple: [Ouidah, languageUsed, 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. FUNO
    FUNO is the stock ticker symbol for Fibra Uno, one of Mexico’s largest real estate investment trusts (REITs) focused on commercial properties.
  • D. Fonyód
    Fonyód is a Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, marinas, and panoramic views of the lake and surrounding hills.
  • E. Fonni
    Fonni is a mountain town in central Sardinia, Italy, known as one of the island’s highest and coldest settlements and a base for exploring the Gennargentu massif.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f84a9d28819084ebfc44fcb2c29c completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f0765b48190b8df68f22c8901f4 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:47 p.m.