Triple

T13306049
Position Surface form Disambiguated ID Type / Status
Subject Croston Parish E316936 entity
Predicate hasSettlement P1068 FINISHED
Object Croston E223761 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: Croston | Statement: [Croston Parish, hasSettlement, Croston]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Croston
Context triple: [Croston Parish, hasSettlement, Croston]
  • A. Croston chosen
    Croston is a historic village in Lancashire, England, known for its picturesque rural setting, traditional architecture, and riverside location.
  • B. Cronton
    Cronton is a small village and civil parish in the Metropolitan Borough of Knowsley in Merseyside, England.
  • C. Standerton
    Standerton is a significant agricultural and commercial town situated on the banks of the Vaal River in South Africa’s Mpumalanga province.
  • D. Dunston
    Dunston is a suburban district on the south bank of the River Tyne in Gateshead, England, known historically for its riverside industry and later redevelopment.
  • E. Shingletown
    Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a76adc8190ab9abcdb79a21ca8 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e3617081909eea9989cf5e7b30 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.