Triple

T8515030
Position Surface form Disambiguated ID Type / Status
Subject Gateshead Works E201550 entity
Predicate regionServed P82 FINISHED
Object Tyneside E651543 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: Tyneside | Statement: [Gateshead Works, regionServed, Tyneside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyneside
Context triple: [Gateshead Works, regionServed, Tyneside]
  • A. Tyneside chosen
    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.
  • B. Tyne and Wear
    Tyne and Wear is a metropolitan county in North East England that includes major urban centers such as Newcastle upon Tyne and Sunderland.
  • C. 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.
  • 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 (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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60e12848190a4a3dfa457aef275 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea84a8a5081909bdcc066e2ba09a4 completed April 2, 2026, 5:32 p.m.
Created at: March 30, 2026, 6:15 p.m.