Triple

T4402638
Position Surface form Disambiguated ID Type / Status
Subject Nice Classification E93651 entity
Predicate adoptedAt P3076 FINISHED
Object Nice, France E101112 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: Nice, France | Statement: [Nice Classification, adoptedAt, Nice, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nice, France
Context triple: [Nice Classification, adoptedAt, Nice, France]
  • A. Nice, France chosen
    Nice, France is a major Mediterranean coastal city on the French Riviera known for its picturesque Promenade des Anglais, vibrant arts scene, and historic old town.
  • B. Douai, France
    Douai, France is a historic town in northern France known for its medieval belfry, legal and university traditions, and role as a regional administrative center.
  • C. Lafrançaise, France
    Lafrançaise is a small commune in the Tarn-et-Garonne department of southern France, known for its rural charm and traditional French village atmosphere.
  • D. Villeblevin, France
    Villeblevin, France is a small commune in north-central France best known as the place where Nobel Prize–winning writer Albert Camus died in a car accident.
  • E. Nancy, France
    Nancy is a historic city in northeastern France known for its elegant 18th-century architecture, especially the UNESCO-listed Place Stanislas.
  • 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_69b345158c748190a2c040fce2da9980 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b352d08a0c8190ac6c125df40eca75 completed March 12, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627e47ff48190b5aea21e4af773de completed March 15, 2026, 3:30 a.m.
Created at: March 12, 2026, 11:28 p.m.