Triple

T19396648
Position Surface form Disambiguated ID Type / Status
Subject Wood Green E485206 entity
Predicate hasPark P105 FINISHED
Object Woodside Park NE NERFINISHED

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: Woodside Park | Statement: [Wood Green, hasPark, Woodside Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Woodside Park
Context triple: [Wood Green, hasPark, Woodside Park]
  • A. Woodside Park chosen
    Woodside Park is a suburban residential area in north London, known for its quiet streets, green spaces, and access to central London via its local station.
  • B. Harwood Park
    Harwood Park is a public recreational park located in Bridgeport, Texas, offering outdoor space and amenities for community activities and leisure.
  • C. Sansom Park
    Sansom Park is a small city located in Tarrant County, Texas, within the Dallas–Fort Worth metropolitan area.
  • D. Brightwood Park
    Brightwood Park is a primarily residential neighborhood in the northwestern quadrant of Washington, D.C., known for its tree-lined streets, rowhouses, and small local businesses.
  • E. Lenora Park
    Lenora Park is a public recreational park in Snellville, Georgia, featuring sports facilities, walking trails, and outdoor amenities for community use.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62573f5788190a635b92121db2cf7 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.