Triple

T5383723
Position Surface form Disambiguated ID Type / Status
Subject Erewash Borough E113151 entity
Predicate hasSettlement P1068 FINISHED
Object Borrowash E117168 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: Borrowash | Statement: [Erewash Borough, hasSettlement, Borrowash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borrowash
Context triple: [Erewash Borough, hasSettlement, Borrowash]
  • A. Borrowash chosen
    Borrowash is a large village in the county of Derbyshire, England, situated just east of the city of Derby.
  • B. Borenore
    Borenore is a small rural locality in the Central West region of New South Wales, Australia, known for its agricultural surroundings and nearby limestone caves.
  • C. Banwen
    Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
  • D. Bisham
    Bisham is a village in Berkshire, England, known for its historic riverside setting on the River Thames and proximity to the town of Marlow.
  • E. Tesseney
    Tesseney is a town in western Eritrea near the Sudanese border, serving as a local commercial and agricultural center in the Gash-Barka region.
  • 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_69bd4436a1988190af18dcff7fd306b4 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd86f39edc81908e53973cef1bc0f3 completed March 20, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf295030b081909bea5e946aac098b completed March 21, 2026, 11:27 p.m.
Created at: March 20, 2026, 2:03 p.m.