Triple

T21550575
Position Surface form Disambiguated ID Type / Status
Subject Reflections on the Motive Power of Fire E531748 entity
Predicate publisher P29 FINISHED
Object Bachelier NE NERFINISHED

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: Bachelier | Statement: [Reflections on the Motive Power of Fire, publisher, Bachelier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bachelier
Context triple: [Reflections on the Motive Power of Fire, publisher, Bachelier]
  • A. Bachelier chosen
    Bachelier was a prominent 19th-century French publishing house known for issuing influential scientific and philosophical works.
  • B. Black–Scholes model
    The Black–Scholes model is a fundamental mathematical framework in financial economics for pricing options and other derivatives by modeling asset prices as stochastic processes.
  • C. Calmann-Lévy
    Calmann-Lévy is a historic French publishing house known for its literary catalog and role in French and European publishing.
  • D. La Bourse
    La Bourse is a short story by Honoré de Balzac that portrays the social and emotional intrigues surrounding a modest painter and a mysterious mother-daughter pair in Parisian society.
  • E. Wentzel
    Wentzel is a surname of German origin borne by various notable individuals across different fields.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb59258b88190966c18f1f519dad6 completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.