Triple

T15472093
Position Surface form Disambiguated ID Type / Status
Subject Beaugrenelle towers E376685 entity
Predicate hasPart P35 FINISHED
Object Tour Reflets E752242 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 Reflets | Statement: [Beaugrenelle towers, hasPart, Tour Reflets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tour Reflets
Context triple: [Beaugrenelle towers, hasPart, Tour Reflets]
  • A. Tour Reflets chosen
    Tour Reflets is a residential high-rise tower located within the modern Front de Seine development in Paris, France.
  • B. Tour Voile
    Tour Voile is a prominent annual offshore sailing race in France featuring multihull and monohull competitions along the French coastline.
  • C. Tour Saphir
    Tour Saphir is a residential high-rise tower in Paris that forms part of the modern Front de Seine development along the Left Bank of the Seine.
  • D. Tour Fenestrelle
    Tour Fenestrelle is a distinctive Romanesque bell tower in Uzès, France, noted for its slender, multi-tiered design and status as an emblem of the town.
  • E. Tour Mercure
    Tour Mercure is a residential high-rise tower located within the Front de Seine complex in Paris, France.
  • 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.