Triple

T14615424
Position Surface form Disambiguated ID Type / Status
Subject Thomas Braun E343072 entity
Predicate hasFamilyName P18 FINISHED
Object Braun E67478 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: Braun | Statement: [Thomas Braun, hasFamilyName, Braun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Braun
Context triple: [Thomas Braun, hasFamilyName, Braun]
  • A. Braun chosen
    Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
  • B. Braun-Pivet
    Braun-Pivet is the surname of Yaël Braun-Pivet, a prominent French politician who has served as President of the National Assembly.
  • C. Brandt
    Brandt is the obsequious personal assistant to the wealthy Jeffrey Lebowski in the cult film "The Big Lebowski," often serving as a nervous intermediary between him and the Dude.
  • D. Brandt
    Brandt is a German surname borne by numerous notable individuals across fields such as politics, science, and the arts.
  • E. Gilette
    Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb45264988190a1df13e8b54a85bd completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda922f29c8190af98a8241d86f7cd completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:25 a.m.