Triple

T19495326
Position Surface form Disambiguated ID Type / Status
Subject TCL bus network E487754 entity
Predicate serves P98 FINISHED
Object Bron 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: Bron | Statement: [TCL bus network, serves, Bron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bron
Context triple: [TCL bus network, serves, Bron]
  • A. Bron
    Bron is a British actress and writer known for her work in film, television, and radio since the 1960s.
  • B. Bron chosen
    Bron is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
  • C. Brun
    Brun is a given name and surname of Germanic origin, closely related to and often used as a variant of Bruno.
  • D. Brandon
    Brandon is a small city in eastern South Dakota that functions largely as a residential and commercial suburb of nearby Sioux Falls.
  • E. Brandon
    Brandon is a town in Suffolk, England, known for its location on the Breckland railway line and its surrounding Breckland heathland and forestry.
  • 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63490c16481908423e304d82722d7 completed April 20, 2026, 2:13 p.m.
Created at: April 10, 2026, 1:40 p.m.