Triple

T4334517
Position Surface form Disambiguated ID Type / Status
Subject Ryan Braun E97432 entity
Predicate familyName 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: [Ryan Braun, familyName, Braun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Braun
Context triple: [Ryan Braun, familyName, 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. Blomberg
    Blomberg is a small town in the Lippe district of North Rhine-Westphalia, Germany, known as the birthplace of former German chancellor Gerhard Schröder.
  • D. Gillette
    Gillette is a globally recognized American brand best known for its razors and shaving products.
  • E. Brinkman
    Brinkman is a surname of Germanic origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351516d488190b5b3d1936e3a325d completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0a9967481908828ceeb76ce4cbf completed March 14, 2026, 9:18 p.m.
Created at: March 12, 2026, 11:14 p.m.