Triple

T258987
Position Surface form Disambiguated ID Type / Status
Subject University of Oxford E5499 entity
Predicate locatedIn P40 FINISHED
Object Oxfordshire E12590 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: Oxfordshire | Statement: [University of Oxford, locatedIn, Oxfordshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxfordshire
Context triple: [University of Oxford, locatedIn, Oxfordshire]
  • A. Oxfordshire chosen
    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.
  • B. Buckinghamshire
    Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
  • C. West Oxfordshire
    West Oxfordshire is a largely rural local government district in Oxfordshire, England, known for its historic market towns, Cotswold landscapes, and villages such as Woodstock.
  • D. West Sussex
    West Sussex is a county in South East England known for its mix of coastal towns, rural countryside, and historic market settlements.
  • E. Hampshire
    Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
  • 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_69a25d71a10c8190894c86e7a67c5974 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3e56fd6b88190b18e081386436ea9 completed March 1, 2026, 7:06 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.