Triple

T15862279
Position Surface form Disambiguated ID Type / Status
Subject Will County E384617 entity
Predicate hasVillage P4011 FINISHED
Object Park Forest 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: Park Forest | Statement: [Will County, hasVillage, Park Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Park Forest
Context triple: [Will County, hasVillage, Park Forest]
  • A. Rolling Meadows
    Rolling Meadows is a suburban city in northeastern Illinois, United States, located in the Chicago metropolitan area.
  • B. Park Forest, Illinois chosen
    Park Forest, Illinois is a suburban village in the Chicago metropolitan area known for its post–World War II planned community design and diverse residential character.
  • C. Park Ridge
    Park Ridge is a residential suburb located within Logan City in Queensland, Australia.
  • D. Arlington Heights
    Arlington Heights is the elevated landform in Arlington, Virginia, that overlooks Washington, D.C. and serves as the site of Arlington National Cemetery and the former Arlington House estate.
  • E. Lake Forest
    Lake Forest is a suburban city in Orange County, California, known for its residential communities, parks, and proximity to major Southern California employment centers.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1555c75688190aeae5bcf5bb92bb7 completed April 16, 2026, 9:32 p.m.
Created at: April 10, 2026, 4:50 a.m.