Triple

T8135355
Position Surface form Disambiguated ID Type / Status
Subject Milo Tindle E189955 entity
Predicate setting P1957 FINISHED
Object Wiltshire, England E153106 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: Wiltshire, England | Statement: [Milo Tindle, setting, Wiltshire, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wiltshire, England
Context triple: [Milo Tindle, setting, Wiltshire, England]
  • A. Wiltshire chosen
    Wiltshire is a historic rural county in South West England known for landmarks such as Stonehenge, Salisbury Cathedral, and its longstanding military presence.
  • B. Berkshire, England
    Berkshire, England is a historic county in South East England known for its royal connections, including Windsor Castle, and its picturesque Thames-side towns.
  • C. Cambridgeshire, England
    Cambridgeshire, England is a historic county in eastern England known for its rural landscapes and as the home of the prestigious University of Cambridge.
  • D. Marlborough, Wiltshire
    Marlborough, Wiltshire is a historic market town in southern England, known for its broad High Street and rich medieval and Georgian heritage.
  • E. 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.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43fff6e0819086c95b571272b50c completed March 31, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced20909481909e44182f1a8fb2a1 completed April 1, 2026, 10:02 a.m.
Created at: March 30, 2026, 5:35 p.m.