Triple

T13279332
Position Surface form Disambiguated ID Type / Status
Subject Albert Lea, Minnesota E316277 entity
Predicate namedAfter P63 FINISHED
Object Albert Lea E316277 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: Albert Lea | Statement: [Albert Lea, Minnesota, namedAfter, Albert Lea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albert Lea
Context triple: [Albert Lea, Minnesota, namedAfter, Albert Lea]
  • A. Albert Lea, Minnesota chosen
    Albert Lea, Minnesota is a small southern Minnesota city known as a regional hub near the Iowa border, surrounded by lakes and intersected by major highways.
  • B. Brainerd
    Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
  • C. Luverne
    Luverne is a small city in southern Alabama that serves as the administrative and commercial hub of Crenshaw County.
  • D. La Crosse
    La Crosse is a mid-sized city in western Wisconsin known for its location along the Mississippi River, historic downtown, and regional educational and healthcare institutions.
  • E. Lansing, Minnesota
    Lansing, Minnesota is a small community located in Mower County in the southeastern part of the state.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99043fba88190872ede6f63e2fbcb completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a56fa048190b32dcef31b978d9c completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:26 p.m.