Triple

T6951428
Position Surface form Disambiguated ID Type / Status
Subject Cours Saleya E160932 entity
Predicate municipality P852 FINISHED
Object City of Nice E140630 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: City of Nice | Statement: [Cours Saleya, municipality, City of Nice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Nice
Context triple: [Cours Saleya, municipality, City of Nice]
  • A. City of Nice chosen
    The City of Nice is a major coastal city on the French Riviera, renowned for its Mediterranean climate, historic old town, and rich artistic and cultural heritage.
  • B. Vieux-Nice
    Vieux-Nice is the historic old town of Nice, France, known for its narrow winding streets, colorful buildings, bustling markets, and vibrant Mediterranean atmosphere.
  • C. Grasse
    Grasse is a town in southeastern France renowned as the world’s perfume capital and a historic center of the fragrance industry.
  • D. Villefranche-sur-Mer
    Villefranche-sur-Mer is a picturesque coastal town in southeastern France known for its deep natural harbor, colorful old town, and scenic setting on the Mediterranean Sea.
  • E. Old Town (Vieux-Nice)
    Old Town (Vieux-Nice) is the historic quarter of Nice, France, known for its narrow winding streets, colorful facades, bustling markets, and vibrant Mediterranean atmosphere.
  • 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_69c68850419081909fb426b8f5a304c7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dab041748190851c5221b6b740e1 completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d36fd638819095d7a431026905f7 completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:29 p.m.