Triple

T9835486
Position Surface form Disambiguated ID Type / Status
Subject Kensington, London, England E239088 entity
Predicate hasGreenSpace P1495 FINISHED
Object Holland Park E119244 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: Holland Park | Statement: [Kensington, London, England, hasGreenSpace, Holland Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holland Park
Context triple: [Kensington, London, England, hasGreenSpace, Holland Park]
  • A. Holland Park chosen
    Holland Park is a leafy, affluent district and public park in west London known for its elegant townhouses, landscaped gardens, and cultural attractions.
  • B. Green Park
    Green Park is a central London royal park known for its open lawns, mature trees, and tranquil atmosphere between Buckingham Palace and Piccadilly.
  • C. Green Park
    Green Park is a public park in Kanpur, India, historically significant enough to lend its name to the nearby Green Park Stadium.
  • D. Green Park
    Green Park is a Delhi Metro station in South Delhi serving the Green Park and nearby Hauz Khas and Safdarjung areas.
  • E. Grosvenor Park
    Grosvenor Park is a large Victorian-era public park in Chester, England, known for its formal gardens, riverside setting, and historic features.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb339aa1c8190901d8e660cef49c5 completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d354c521dc819084b09c9a57c1a26c completed April 6, 2026, 6:37 a.m.
Created at: March 30, 2026, 8:33 p.m.