Triple

T20934938
Position Surface form Disambiguated ID Type / Status
Subject Nottingham–Derby metropolitan area E515558 entity
Predicate hasMajorTown P316 FINISHED
Object Borrowash 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: Borrowash | Statement: [Nottingham–Derby metropolitan area, hasMajorTown, Borrowash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borrowash
Context triple: [Nottingham–Derby metropolitan area, hasMajorTown, 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. Bengeo
    Bengeo is a residential suburb and historic area of Hertford in Hertfordshire, England.
  • E. 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.
  • 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_69e0b4fc13408190b06868df03c5c29b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f950d5e081908ec0df4824cf69f7 completed April 21, 2026, 4:13 a.m.
Created at: April 16, 2026, 12:49 p.m.