Triple

T2990514
Position Surface form Disambiguated ID Type / Status
Subject River Sankey E80738 entity
Predicate region P40 FINISHED
Object Merseyside E12624 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: Merseyside | Statement: [River Sankey, region, Merseyside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merseyside
Context triple: [River Sankey, region, Merseyside]
  • A. Merseyside chosen
    Merseyside is a metropolitan county in North West England that includes the city of Liverpool and its surrounding urban areas.
  • 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. Wirral
    Wirral is a peninsula in North West England known for its mix of coastal towns, suburban areas, and countryside between the River Mersey and the River Dee.
  • D. Lancashire
    Lancashire is a historic county in North West England known for its role in the Industrial Revolution and major towns such as Lancaster, Preston, and Blackpool.
  • E. 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.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99de55208190bc56ecbe08638e5a completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108cc4870819081e68032517468a8 completed March 11, 2026, 6:16 a.m.
Created at: March 8, 2026, 2:59 p.m.