Triple

T14746197
Position Surface form Disambiguated ID Type / Status
Subject Taverham E346473 entity
Predicate hasNeighbouringSettlement P4647 FINISHED
Object Costessey E345273 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: Costessey | Statement: [Taverham, hasNeighbouringSettlement, Costessey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Costessey
Context triple: [Taverham, hasNeighbouringSettlement, Costessey]
  • A. Costessey chosen
    Costessey is a village and civil parish in Norfolk, England, situated just west of Norwich.
  • B. Tealby
    Tealby is a picturesque rural village in eastern England, known for its traditional stone cottages and scenic setting within the Lincolnshire countryside.
  • C. Paston
    Paston is an English surname historically associated with a prominent gentry family from Norfolk, known for the medieval Paston Letters.
  • D. Pytchley
    Pytchley is a small village and civil parish in North Northamptonshire, England, known historically for its association with the Pytchley Hunt.
  • E. Coryton
    Coryton is a suburban area and railway terminus in Cardiff, Wales, served by local commuter trains.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d002708190a32a4a45e96fc389 completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb982b5c8190a0340be2186f8b81 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:30 a.m.