Triple

T7721960
Position Surface form Disambiguated ID Type / Status
Subject Near South Side, Chicago E175033 entity
Predicate borders P224 FINISHED
Object Douglas, Chicago E669630 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: Douglas, Chicago | Statement: [Near South Side, Chicago, borders, Douglas, Chicago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglas, Chicago
Context triple: [Near South Side, Chicago, borders, Douglas, Chicago]
  • A. Douglas, Chicago chosen
    Douglas is a South Side neighborhood in Chicago known for its historic Bronzeville district, rich African American cultural heritage, and lakefront parks.
  • B. Avondale, Chicago
    Avondale, Chicago is a diverse, historically working-class neighborhood on Chicago’s Northwest Side known for its strong Polish and Latino communities and growing residential redevelopment.
  • C. Douglas
    Douglas is the capital and largest town of the Isle of Man, serving as its main commercial center and principal ferry port.
  • D. Douglas
    Douglas is a historic Scottish noble house that played a major role in the political and military history of medieval and early modern Scotland.
  • E. Douglas
    Douglas is a small lakeside city in Allegan County, Michigan, known for its arts community and proximity to Lake Michigan beaches.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702f1786881908b025d8986e5f1fa completed March 27, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b51b612881909f20a6b777db348c completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:05 p.m.