Triple

T1208563
Position Surface form Disambiguated ID Type / Status
Subject Castleton E25945 entity
Predicate nearestTown P350 FINISHED
Object Hope E113156 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: Hope | Statement: [Castleton, nearestTown, Hope]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hope
Context triple: [Castleton, nearestTown, Hope]
  • A. Hope chosen
    Hope is a small village in the Peak District of Derbyshire, England, known for its scenic surroundings and role as a local tourist and walking hub.
  • B. Hope
    Hope is the official motto of the former Colony of Rhode Island and Providence Plantations, reflecting the colony’s historical emphasis on religious freedom and optimism.
  • C. Hope
    Hope is a feminine given name often associated with optimism and positive expectation.
  • D. HOPE
    HOPE is a famous pop art sculpture and graphic work by Robert Indiana that echoes his iconic LOVE design, featuring the word “HOPE” in bold, stacked letters.
  • E. Hope and Suffering
    Hope and Suffering is a collection of sermons and reflections by Archbishop Desmond Tutu that explores faith, justice, and resilience amid the struggle against apartheid in South Africa.
  • 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_69a4942b30f08190a91c60573e16b5ef completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bde18d208190848c189b2b8d585f completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f419b8c8190ac7642b9b4108df8 completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:46 p.m.