Triple

T1753430
Position Surface form Disambiguated ID Type / Status
Subject North Yorkshire E38497 entity
Predicate contains P35 FINISHED
Object Ripon E145308 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: Ripon | Statement: [North Yorkshire, contains, Ripon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ripon
Context triple: [North Yorkshire, contains, Ripon]
  • A. Ripon
    Ripon is a small city in California’s Central Valley known for its agricultural roots and tight-knit community.
  • B. City of York
    The City of York is a historic cathedral city in North Yorkshire, England, renowned for its medieval walls, Gothic York Minster, and well-preserved old town.
  • C. Chester
    Chester is a small, historically industrial city in southeastern Pennsylvania that lies just southwest of Philadelphia along the Delaware River.
  • D. Chester
    Chester is the given name of Chester W. Nimitz, the prominent U.S. Navy fleet admiral who played a leading role in the Pacific theater during World War II.
  • E. Ripon, North Yorkshire chosen
    Ripon, North Yorkshire is a historic cathedral city in northern England known for its medieval architecture and ancient religious heritage.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64169c508190a33074fb06e9c755 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e84c1c8190917edf14003cba81 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.