Triple

T22308938
Position Surface form Disambiguated ID Type / Status
Subject Swing Bridge E551461 entity
Predicate location P40 FINISHED
Object Tyne and Wear 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: Tyne and Wear | Statement: [Swing Bridge, location, Tyne and Wear]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyne and Wear
Context triple: [Swing Bridge, location, Tyne and Wear]
  • A. Tyne and Wear chosen
    Tyne and Wear is a metropolitan county in North East England that includes major urban centers such as Newcastle upon Tyne and Sunderland.
  • B. Washington, Tyne and Wear
    Washington, Tyne and Wear is a town in North East England that forms part of the City of Sunderland and is historically associated with the ancestors of U.S. President George Washington.
  • C. Tyneside
    Tyneside is an urban region in northeast England centered on the River Tyne, best known for the city of Newcastle and its strong football and industrial heritage.
  • D. Merseyside
    Merseyside is a metropolitan county in North West England that includes the city of Liverpool and its surrounding urban areas.
  • E. Teesside
    Teesside is an urban area in North East England centered around the River Tees, encompassing towns such as Middlesbrough and Stockton-on-Tees and known for its industrial heritage.
  • 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_69e11e46c0188190800181a4233f28fe completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1574c8a248190bf5eef5be78381fd completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:42 p.m.