Triple

T16727503
Position Surface form Disambiguated ID Type / Status
Subject Wilmette Pumping Station E406499 entity
Predicate serves P98 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: [Wilmette Pumping Station, serves, Wilmette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilmette
Context triple: [Wilmette Pumping Station, serves, 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. 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.
  • D. Berwyn
    Berwyn is a residential neighborhood within College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • E. Schaumburg
    Schaumburg is a historic German county and region that once formed part of the territorial holdings of various German princes and states.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38748f538819097de1fdee9b42f34 completed April 18, 2026, 1:29 p.m.
Created at: April 10, 2026, 5:20 a.m.