Triple

T21013979
Position Surface form Disambiguated ID Type / Status
Subject Hinckley and Bosworth E517621 entity
Predicate hasSettlement P1068 FINISHED
Object Hinckley 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: Hinckley | Statement: [Hinckley and Bosworth, hasSettlement, Hinckley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hinckley
Context triple: [Hinckley and Bosworth, hasSettlement, Hinckley]
  • A. Hinckley
    Hinckley is a small town in central Utah, United States, known for its rural agricultural setting and proximity to the Sevier Desert.
  • B. Hinckley chosen
    Hinckley is a market town in southwest Leicestershire, England, known historically for its hosiery industry and its location between Coventry and Leicester.
  • C. Mansfield
    Mansfield is a small borough in northern Pennsylvania known for its rural setting and the presence of Mansfield University of Pennsylvania.
  • D. Mansfield
    Mansfield is a historic Scottish territorial designation traditionally linked to the noble House of Murray.
  • E. Mansfield
    Mansfield is a large market town in Nottinghamshire, England, known historically for its coal mining industry and proximity to Sherwood Forest.
  • 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc5764188190829de6f5abd6e00f completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:54 p.m.