Triple

T15472099
Position Surface form Disambiguated ID Type / Status
Subject Beaugrenelle towers E376685 entity
Predicate hasPart P35 FINISHED
Object Tour Mercure E752244 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: Tour Mercure | Statement: [Beaugrenelle towers, hasPart, Tour Mercure]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tour Mercure
Context triple: [Beaugrenelle towers, hasPart, Tour Mercure]
  • A. Tour Mercure chosen
    Tour Mercure is a residential high-rise tower located within the Front de Seine complex in Paris, France.
  • B. Tour Bonbec
    Tour Bonbec is a historic medieval tower of the Conciergerie in Paris, notable for its role in the former royal palace and prison complex on the Île de la Cité.
  • C. Tour Magne
    Tour Magne is an ancient Roman watchtower in Nîmes, France, notable as one of the city’s most prominent historical monuments.
  • D. Tour Reflets
    Tour Reflets is a residential high-rise tower located within the modern Front de Seine development in Paris, France.
  • E. Tour Total
    Tour Total is a prominent skyscraper and major office tower in the La Défense business district near Paris, serving as a key part of the area’s modern skyline.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6c57308190b4cfe661c26addd4 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d0543f881909dfbbc77f2a96a1a completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:33 a.m.