Triple

T77491
Position Surface form Disambiguated ID Type / Status
Subject Detlev W. Bronk E1549 entity
Predicate hasSurname P18 FINISHED
Object Bronk E1549 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: Bronk | Statement: [Detlev W. Bronk, hasSurname, Bronk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bronk
Context triple: [Detlev W. Bronk, hasSurname, Bronk]
  • A. Bronk chosen
    Bronk is a surname most notably associated with Detlev W. Bronk, an influential American scientist and educator who helped shape modern biophysics and higher education policy.
  • B. Angus
    Angus is a historic county and region on the east coast of Scotland known for its rural landscapes, agriculture, and coastal towns.
  • C. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • D. Texas Eagle
    The Texas Eagle is a long-distance Amtrak passenger train route running between Chicago and San Antonio, known for traversing the central United States through states like Illinois, Missouri, Arkansas, and Texas.
  • E. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f1d20b88190b66836cc018e52e1 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26241d4c08190885dab6aef75dcf3 completed Feb. 28, 2026, 3:34 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.