Triple

T1819083
Position Surface form Disambiguated ID Type / Status
Subject Runashimi E40500 entity
Predicate hasDialects P4251 FINISHED
Object Imbabura Kichwa E39500 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: Imbabura Kichwa | Statement: [Runashimi, hasDialects, Imbabura Kichwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imbabura Kichwa
Context triple: [Runashimi, hasDialects, Imbabura Kichwa]
  • A. Imbabura Kichwa chosen
    Imbabura Kichwa is a regional variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in Ecuador’s Imbabura province.
  • B. Chocontá
    Chocontá is a municipality and town in central Colombia known for its agricultural production and colonial-era history.
  • C. Zipaquirá
    Zipaquirá is a historic Colombian city famed for its underground Salt Cathedral and colonial architecture, located north of Bogotá.
  • D. Huaral
    Huaral is a coastal agricultural city in central Peru known for its fruit production and proximity to Lima.
  • E. Chiquinquirá
    Chiquinquirá is a Colombian town known as a major religious pilgrimage center and the site of the Basilica of Our Lady of the Rosary of Chiquinquirá.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65f8c4e48190925aec9916dd6c30 completed March 6, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9ac97e081908ab1d30fa41c3e9b completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:32 p.m.