Triple

T13463120
Position Surface form Disambiguated ID Type / Status
Subject Tour Incity E311421 entity
Predicate locatedIn P40 FINISHED
Object Part-Dieu business district E487674 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: Part-Dieu business district | Statement: [Tour Incity, locatedIn, Part-Dieu business district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Part-Dieu business district
Context triple: [Tour Incity, locatedIn, Part-Dieu business district]
  • A. Quartier Part-Dieu chosen
    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.
  • B. 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.
  • C. Beaubourg neighborhood
    The Beaubourg neighborhood is a lively area in central Paris known for its modern art, street life, and the iconic Centre Pompidou.
  • D. Les Halles neighborhood
    Les Halles neighborhood is a central Paris district known for its major underground shopping mall, transport hub, and lively commercial and cultural scene.
  • E. Vaugirard centers
    Vaugirard centers are a group of Paris-based academic facilities of Université Paris 2 Panthéon-Assas that host various law and social sciences teaching and research activities.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf0d95fc81909d9f73d5315dc7b4 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d8ab8548190a0a1adbe927c95d0 completed May 3, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:41 p.m.