Triple

T20481739
Position Surface form Disambiguated ID Type / Status
Subject Purple Line (CTA) E502471 entity
Predicate primarySuburbServed P82 FINISHED
Object Wilmette 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: Wilmette | Statement: [Purple Line (CTA), primarySuburbServed, Wilmette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilmette
Context triple: [Purple Line (CTA), primarySuburbServed, Wilmette]
  • A. Wilmette, Illinois chosen
    Wilmette, Illinois is a suburban village on the North Shore of the Chicago metropolitan area, known for its affluent residential character, lakefront location, and highly rated public schools.
  • B. 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.
  • C. Lake Forest
    Lake Forest is a residential lake community located within Jefferson Township in Morris County, New Jersey.
  • D. Berwyn
    Berwyn is a suburban community in Pennsylvania known for its residential character, local shops, and access to regional rail within the greater Philadelphia area.
  • E. Berwyn
    Berwyn is a residential neighborhood within College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • 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_69e0b4af32848190aea80682b44d5d6e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69b57fa9c819091d12320d46a0cee completed April 20, 2026, 9:32 p.m.
Created at: April 16, 2026, 11:34 a.m.