Triple

T15350313
Position Surface form Disambiguated ID Type / Status
Subject Hundred of Salford E367033 entity
Predicate contains P35 FINISHED
Object Farnworth E496807 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: Farnworth | Statement: [Hundred of Salford, contains, Farnworth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Farnworth
Context triple: [Hundred of Salford, contains, Farnworth]
  • A. Farnworth chosen
    Farnworth is a town in Greater Manchester, England, historically part of Lancashire and now largely residential with local industry and transport links to nearby urban centers.
  • B. Barrasford
    Barrasford is a small village in Northumberland, England, situated in the Tyne Valley and known for its rural setting and proximity to Hadrian’s Wall.
  • C. Cornbrook
    Cornbrook is a major Metrolink tram interchange area in Manchester, England, providing key connections between multiple tram lines.
  • D. Fritchley
    Fritchley is a small village in Derbyshire, England, known for its rural character and proximity to the larger village of Crich.
  • E. Worsthorne
    Worsthorne is a British surname most notably associated with journalist and commentator Peregrine Worsthorne.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e290efc8190b22c95dcd3e5f57f completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01fd53688190939787a3d6ff3bb9 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:17 a.m.