Triple

T261911
Position Surface form Disambiguated ID Type / Status
Subject William Penn E5557 entity
Predicate burialPlace P196 FINISHED
Object Buckinghamshire E10606 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: Buckinghamshire | Statement: [William Penn, burialPlace, Buckinghamshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buckinghamshire
Context triple: [William Penn, burialPlace, Buckinghamshire]
  • A. Buckinghamshire chosen
    Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
  • B. Oxfordshire
    Oxfordshire is a historic county in South East England known for the city of Oxford and its prestigious university, as well as its stately homes and rural landscapes.
  • C. West Sussex
    West Sussex is a county in South East England known for its mix of coastal towns, rural countryside, and historic market settlements.
  • D. Surrey
    Surrey is a county in southeast England known for its historic towns, affluent suburbs, and proximity to London.
  • E. Staffordshire
    Staffordshire is a landlocked county in the West Midlands of England known for its industrial heritage, particularly in pottery and brewing, and its mix of rural landscapes and historic towns.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3eca25d9081909fe6d2ed2cda16d9 completed March 1, 2026, 7:37 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.