Triple

T10180685
Position Surface form Disambiguated ID Type / Status
Subject Auber E235972 entity
Predicate connectsArea P2564 FINISHED
Object Opéra district E248501 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: Opéra district | Statement: [Auber, connectsArea, Opéra district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opéra district
Context triple: [Auber, connectsArea, Opéra district]
  • A. Opéra district chosen
    The Opéra district is a central Parisian neighborhood famed for its grand boulevards, luxury shopping, and the Palais Garnier opera house.
  • B. Beaugrenelle district
    The Beaugrenelle district is a modern riverside neighborhood in Paris known for its high-rise architecture, shopping center, and contemporary urban design along the Seine.
  • C. Sentier district
    The Sentier district is a historic central Paris neighborhood known for its former textile and garment industry, narrow streets, and more recently its concentration of tech startups and media companies.
  • D. Le Panier district
    Le Panier district is Marseille’s oldest neighborhood, known for its narrow streets, colorful facades, and vibrant mix of historic charm, street art, and local cafés.
  • E. Quartier Part-Dieu
    Quartier Part-Dieu is Lyon’s main business district, known for its high-rise offices, major shopping center, and one of France’s busiest railway stations.
  • 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_69ca84d1d5f88190ab878a1021ecff68 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded315f14819085727bd9b4363d10 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d301373a008190b8d39a8db4167e4f completed April 6, 2026, 12:41 a.m.
Created at: March 30, 2026, 9:11 p.m.