Triple

T11890183
Position Surface form Disambiguated ID Type / Status
Subject Auburn-Opelika metropolitan area E282890 entity
Predicate containsCity P294 FINISHED
Object Auburn, Alabama E98092 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: Auburn, Alabama | Statement: [Auburn-Opelika metropolitan area, containsCity, Auburn, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Auburn, Alabama
Context triple: [Auburn-Opelika metropolitan area, containsCity, Auburn, Alabama]
  • A. Auburn, Georgia
    Auburn, Georgia is a small city in Barrow and Gwinnett counties within the Atlanta metropolitan area.
  • B. Auburn chosen
    Auburn is a city in eastern Alabama known for being home to Auburn University and its strong college-town atmosphere.
  • C. Auburn
    Auburn is a city in south-central Maine known for its historic architecture, role as a regional service and economic center, and its location along the Androscoggin River opposite Lewiston.
  • D. Auburn
    Auburn is a residential neighborhood located within the city of Cranston, Rhode Island.
  • E. Auburn
    Auburn is a small city in northeastern Indiana known for its automotive heritage and classic car museums.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a3f7548190adfb567f060a175a completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f48a4d0e908190b6465b1094373e2c completed May 1, 2026, 11:11 a.m.
Created at: April 8, 2026, 9:44 p.m.