Triple

T7291827
Position Surface form Disambiguated ID Type / Status
Subject Woodhaven E164414 entity
Predicate hasPark P105 FINISHED
Object Forest Park E509227 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: Forest Park | Statement: [Woodhaven, hasPark, Forest Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forest Park
Context triple: [Woodhaven, hasPark, Forest Park]
  • A. Forest Park
    Forest Park is a large urban public park in St. Louis known for hosting major cultural institutions, museums, and recreational spaces, and for being one of the largest city parks in the United States.
  • B. Forest Park
    Forest Park is a vast, heavily forested urban park in Portland, Oregon, known for its extensive trail system and rich wildlife habitat.
  • C. Forest Park
    Forest Park is a large historic urban park in Springfield, Massachusetts, known for its extensive green spaces, recreational facilities, and seasonal attractions.
  • D. Forest Park chosen
    Forest Park is a large urban green space in central Queens, New York City, known for its extensive woodlands, trails, and recreational facilities.
  • E. Forest Park
    Forest Park is a western Chicago suburb that serves as the terminus of the Chicago Transit Authority’s Blue Line rapid transit route.
  • 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_69c6887a499881909dd23341399c59d8 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6eb6e8f3881908628b3d41aad70c6 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2693f054081909fe58a252bd76226 completed April 5, 2026, 1:53 p.m.
Created at: March 27, 2026, 3 p.m.