Triple

T20476949
Position Surface form Disambiguated ID Type / Status
Subject Draycott E502340 entity
Predicate hasNearbySettlement P4647 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: [Draycott, hasNearbySettlement, Borrowash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borrowash
Context triple: [Draycott, hasNearbySettlement, 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_69e0b4af32848190aea80682b44d5d6e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6996584648190a1a6dfcb57782b7f completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:34 a.m.