Triple

T19572185
Position Surface form Disambiguated ID Type / Status
Subject The Little Apple E489745 entity
Predicate county P75 FINISHED
Object Riley County 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: Riley County | Statement: [The Little Apple, county, Riley County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riley County
Context triple: [The Little Apple, county, Riley County]
  • A. Riley County, Kansas chosen
    Riley County, Kansas is a county in northeastern Kansas known for being home to the city of Manhattan and Kansas State University.
  • B. Hutchinson County
    Hutchinson County is a rural county in the Texas Panhandle known for its oil and gas production and small, closely knit communities.
  • C. Pawnee County
    Pawnee County is a rural county in central Kansas known for its agricultural landscape and small communities such as Burdett.
  • D. Cloud County, Kansas
    Cloud County, Kansas is a rural county in north-central Kansas known for its agricultural landscape, small communities, and location along the Republican River.
  • E. Chase County
    Chase County is a rural county in east-central Kansas known for its tallgrass prairie landscapes within the Flint Hills region.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6402103208190b80acdfa82b7a9c4 completed April 20, 2026, 3:02 p.m.
Created at: April 10, 2026, 1:42 p.m.