Triple

T3778617
Position Surface form Disambiguated ID Type / Status
Subject Newcastle International Airport E83367 entity
Predicate serves P98 FINISHED
Object Tyneside E304544 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: [Newcastle International Airport, serves, Tyneside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyneside
Context triple: [Newcastle International Airport, serves, Tyneside]
  • A. 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.
  • 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. Merseyside
    Merseyside is a metropolitan county in North West England that includes the city of Liverpool and its surrounding urban areas.
  • D. Wearside
    Wearside is an area in North East England centered on the city of Sunderland and the valley of the River Wear.
  • E. Tyneside urban area chosen
    The Tyneside urban area is a large conurbation in North East England centered on Newcastle upon Tyne and Gateshead, encompassing numerous surrounding towns along the River Tyne.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc78173081908b230017834cdf9e completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5282f253c81908c18a30bb1025f99 completed March 14, 2026, 9:19 a.m.
Created at: March 8, 2026, 3:36 p.m.