Triple

T15411345
Position Surface form Disambiguated ID Type / Status
Subject Benacre E368599 entity
Predicate locatedIn P40 FINISHED
Object Waveney District E283777 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: Waveney District | Statement: [Benacre, locatedIn, Waveney District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waveney District
Context triple: [Benacre, locatedIn, Waveney District]
  • A. Waveney district chosen
    Waveney district was a former local government district in Suffolk, England, centered on the town of Lowestoft and named after the River Waveney.
  • B. Tendring district
    Tendring district is a local government district in Essex, England, known for its coastal towns and seaside resorts including Clacton-on-Sea.
  • C. Rochford District
    Rochford District is a local government district in Essex, England, encompassing both rural communities and parts of the Southend urban area, including London Southend Airport.
  • D. Fenland District
    Fenland District is a local government district in the county of Cambridgeshire in eastern England, known for its flat, low-lying agricultural landscape and market towns.
  • E. Babergh district
    Babergh district is a local government district in Suffolk, England, known for its rural landscapes, historic villages, and market towns such as Sudbury and Hadleigh.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea600b48190a3dbca1a68a2a1cd completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d40d3388190b1bd724238f928b1 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:20 a.m.