Triple

T15138258
Position Surface form Disambiguated ID Type / Status
Subject Rough for Theatre II E361613 entity
Predicate hasCharacter P2308 FINISHED
Object Bertrand E11918 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: Bertrand | Statement: [Rough for Theatre II, hasCharacter, Bertrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bertrand
Context triple: [Rough for Theatre II, hasCharacter, Bertrand]
  • A. Bertrand chosen
    Bertrand is a masculine given name most famously associated with the British philosopher, logician, and Nobel laureate Bertrand Russell.
  • B. Bertrand-Sévère
    Bertrand-Sévère is the given name of Bertrand-Sévère Mascarou-Laurence, a French individual identifiable primarily through this full personal name.
  • C. Bertrand-Jean
    Bertrand-Jean is the birth name of the French Symbolist painter and printmaker better known as Odilon Redon.
  • D. Honoré
    Honoré is the given name of the renowned 19th-century French novelist and playwright Honoré de Balzac.
  • E. Ambroise
    Ambroise is a modern digital revival of classic Didone-style typefaces, characterized by high contrast between thick and thin strokes and elegant, refined letterforms.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005b59b488190b0016970647e7483 completed April 15, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfea8e3081909551a8e3936c13a6 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:07 a.m.