Triple

T20332197
Position Surface form Disambiguated ID Type / Status
Subject Santa Ana Pueblo E492511 entity
Predicate hasLanguage P15 FINISHED
Object Eastern Keres 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: Eastern Keres | Statement: [Santa Ana Pueblo, hasLanguage, Eastern Keres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eastern Keres
Context triple: [Santa Ana Pueblo, hasLanguage, Eastern Keres]
  • A. Eastern Keres chosen
    Eastern Keres is a Keresan Puebloan language traditionally spoken by Native American communities in central New Mexico.
  • B. Western Keres
    Western Keres is a Keresan Puebloan language spoken by the Keres people of western New Mexico.
  • C. Keteyian
    Keteyian is the surname of Armen Keteyian, an American television journalist and author known for his investigative sports reporting.
  • D. Kataiysk
    Kataiysk is a small town in southwestern Siberia, Russia, serving as a local administrative and economic center within Kurgan Oblast.
  • E. Kiserian
    Kiserian is a rapidly growing town in Kenya’s Kajiado County, situated just southwest of Nairobi and known as a residential and trading hub for the surrounding Maasai pastoral communities.
  • 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_69e0b4a1a09881908d97270d6971a25a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e677e886a08190952b828fedd2a411 completed April 20, 2026, 7 p.m.
Created at: April 16, 2026, 11:22 a.m.