Triple

T24335104
Position Surface form Disambiguated ID Type / Status
Subject Kanosh Band of Paiutes E613357 entity
Predicate associatedWithTown P19735 FINISHED
Object Kanosh, Utah
Kanosh, Utah is a small town in Millard County named after a Paiute chief and known for its historical ties to the Kanosh Band of Paiutes and early Mormon settlement.
E1842023 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: Kanosh, Utah | Statement: [Kanosh Band of Paiutes, associatedWithTown, Kanosh, Utah]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kanosh, Utah
Triple: [Kanosh Band of Paiutes, associatedWithTown, Kanosh, Utah]
Generated description
Kanosh, Utah is a small town in Millard County named after a Paiute chief and known for its historical ties to the Kanosh Band of Paiutes and early Mormon settlement.

Provenance (5 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_69e2d7dcc5a08190b53691130d56cbc4 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f444b08190b9c8e033ff6ee5fc completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec0f80a88190aa6f4c69962d7359 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f092aabc81908676a4d355891072 completed June 7, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_6a24f55704a081908533c0e5d81b1bb2 completed June 7, 2026, 4:36 a.m.
Created at: April 18, 2026, 1:56 a.m.