Triple

T8965387
Position Surface form Disambiguated ID Type / Status
Subject Bloomington E214116 entity
Predicate borders P224 FINISHED
Object Edina E353222 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: Edina | Statement: [Bloomington, borders, Edina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edina
Context triple: [Bloomington, borders, Edina]
  • A. Edina chosen
    Edina is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its affluent neighborhoods, strong school system, and major shopping centers like Southdale Center.
  • B. Berwyn
    Berwyn is a residential neighborhood within College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • C. Nicoma Park
    Nicoma Park is a small city in central Oklahoma known as a residential community within the Oklahoma City metropolitan area.
  • D. Schaumburg
    Schaumburg is a historic German county and region that once formed part of the territorial holdings of various German princes and states.
  • E. Haslett
    Haslett is a suburban community in Michigan known for its residential neighborhoods and proximity to East Lansing and Michigan State University.
  • 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_69ca839cd6008190a1546a701a56710c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc674c4be8819090d46aba8ab40af3 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc95514408190ad442069daec0459 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:01 p.m.