Triple

T8646039
Position Surface form Disambiguated ID Type / Status
Subject Childrey E204979 entity
Predicate historicCounty P1069 FINISHED
Object Berkshire E83859 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: Berkshire | Statement: [Childrey, historicCounty, Berkshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berkshire
Context triple: [Childrey, historicCounty, Berkshire]
  • A. Berkshire chosen
    Berkshire is a historic county in South East England known for its royal connections, including Windsor Castle, and its mix of affluent towns and rural landscapes.
  • B. Berkshire County
    Berkshire County is a rural, culturally rich county in western Massachusetts known for its scenic Berkshire Mountains, outdoor recreation, and vibrant arts institutions.
  • C. 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.
  • D. Hampshire County
    Hampshire County is a county in western Massachusetts known for its college towns, including Amherst and Northampton, and its vibrant academic and cultural communities.
  • E. Rutland
    Rutland is a small town in Worcester County, Massachusetts, known for its rural character and location near the geographic center of the state.
  • 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_69ca834e56848190abb0eeaec9dedd32 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc480eb7f88190a38d2150976cd47f completed March 31, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebc4883cc8190a6fb72005ca99512 completed April 2, 2026, 6:58 p.m.
Created at: March 30, 2026, 6:28 p.m.