Triple

T4259661
Position Surface form Disambiguated ID Type / Status
Subject Épernay E96071 entity
Predicate hasLandmark P105 FINISHED
Object Avenue de Champagne E573174 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: Avenue de Champagne | Statement: [Épernay, hasLandmark, Avenue de Champagne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avenue de Champagne
Context triple: [Épernay, hasLandmark, Avenue de Champagne]
  • A. Avenue de Champagne chosen
    Avenue de Champagne is a prestigious street in Épernay, France, renowned for its historic champagne houses and extensive underground cellars.
  • B. Avenue de France
    Avenue de France is a central thoroughfare in downtown Tunis, Tunisia, known for its historic architecture and its role as a key commercial and urban artery.
  • C. Avenue de Breteuil
    Avenue de Breteuil is a broad, tree-lined avenue in Paris’s 7th arrondissement, known for its central green esplanade and views toward Les Invalides.
  • D. Avenue de Verdun
    Avenue de Verdun is a prominent street in central Nice, France, running near the seafront and bordering key landmarks such as the Jardin Albert Ier.
  • E. Avenue de Ségur
    Avenue de Ségur is a major Parisian avenue in the 7th arrondissement, known for its government buildings and proximity to landmarks like the École Militaire and the UNESCO headquarters.
  • 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34f7fe7348190baed8d214268b756 completed March 12, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16e581e94819086313b9d3a40b159 completed March 23, 2026, 4:46 p.m.
Created at: March 12, 2026, 11:06 p.m.