Triple

T2071955
Position Surface form Disambiguated ID Type / Status
Subject Williamsburg E44832 entity
Predicate hasPark P105 FINISHED
Object McCarren Park E41588 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: McCarren Park | Statement: [Williamsburg, hasPark, McCarren Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: McCarren Park
Context triple: [Williamsburg, hasPark, McCarren Park]
  • A. McCarren Park chosen
    McCarren Park is a popular public park in North Brooklyn known for its athletic fields, pool, and frequent cultural events and concerts.
  • B. Kingman Park
    Kingman Park is a residential neighborhood in Northeast Washington, D.C., known for its early-20th-century rowhouses and proximity to the Anacostia River and RFK Stadium.
  • C. Tumbleweed Park
    Tumbleweed Park is a public recreational park in Chandler, Arizona, featuring open green spaces, sports facilities, and family-friendly amenities.
  • D. Grand Park
    Grand Park is a large urban civic park in the heart of downtown Los Angeles known for its open lawns, fountains, and public events.
  • E. Alta Plaza Park
    Alta Plaza Park is a terraced hilltop park in San Francisco known for its sweeping city views, playgrounds, and tennis courts.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0d20bc8190b19a32157f8b1607 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6aea7f58819081790c08791a5841 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:41 p.m.