Triple

T21269405
Position Surface form Disambiguated ID Type / Status
Subject Nottingham–Skegness line E524215 entity
Predicate passesThrough P225 FINISHED
Object Bingham 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: Bingham | Statement: [Nottingham–Skegness line, passesThrough, Bingham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bingham
Context triple: [Nottingham–Skegness line, passesThrough, Bingham]
  • A. Bingham chosen
    Bingham is a small market town in Nottinghamshire, England, known for its historic center and role as a local commercial and residential hub.
  • B. Bingham
    Bingham is a residential suburb in the east of Edinburgh, Scotland, known for its post-war housing and proximity to major transport routes.
  • C. Bingham
    Bingham is a surname most notably associated with the 19th-century American painter George Caleb Bingham.
  • D. Ellnora
    Ellnora is a feminine given name most notably borne by American philanthropist Ellnora Decker Krannert, a major benefactor of arts and education.
  • E. Pangborn
    Pangborn is a surname most notably associated with American character actor Franklin Pangborn, known for his comedic roles in early 20th-century films.
  • 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_69e0b5156d7881909bd4f83676590715 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73651115081908b5083ba818a6bb1 completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:01 p.m.