Triple

T309622
Position Surface form Disambiguated ID Type / Status
Subject Kichwa E6374 entity
Predicate hasDialect P4251 FINISHED
Object Pastaza Kichwa
Pastaza Kichwa is a variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in the Pastaza region of the Ecuadorian Amazon.
 E6374 NE FINISHED

How this triple was built (4 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: Pastaza Kichwa | Statement: [Kichwa, hasDialect, Pastaza Kichwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pastaza Kichwa
Context triple: [Kichwa, hasDialect, Pastaza Kichwa]
  • A. Kichwa
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • B. Aymara
    Aymara is an indigenous language spoken primarily by the Aymara people of the central Andes in countries such as Bolivia, Peru, and Chile.
  • C. Imbabura Kichwa
    Imbabura Kichwa is a regional variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in Ecuador’s Imbabura province.
  • D. Pacho
    Pacho is a town and municipality in the Cundinamarca Department of central Colombia, known historically for its agricultural production and scenic Andean surroundings.
  • E. Sopó
    Sopó is a small municipality in the department of Cundinamarca, Colombia, known for its scenic Andean landscapes and dairy production.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Pastaza Kichwa
Triple: [Kichwa, hasDialect, Pastaza Kichwa]
Generated description
Pastaza Kichwa is a variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in the Pastaza region of the Ecuadorian Amazon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pastaza Kichwa
Target entity description: Pastaza Kichwa is a variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in the Pastaza region of the Ecuadorian Amazon.
  • A. Kichwa chosen
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • B. Aymara
    Aymara is an indigenous language spoken primarily by the Aymara people of the central Andes in countries such as Bolivia, Peru, and Chile.
  • C. Imbabura Kichwa
    Imbabura Kichwa is a regional variety of the Kichwa (Quechuan) language spoken primarily by Indigenous communities in Ecuador’s Imbabura province.
  • D. Pacho
    Pacho is a town and municipality in the Cundinamarca Department of central Colombia, known historically for its agricultural production and scenic Andean surroundings.
  • E. Sopó
    Sopó is a small municipality in the department of Cundinamarca, Colombia, known for its scenic Andean landscapes and dairy production.
  • F. None of above.

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_69a2e79230508190b912ecb555aae17e completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea33ba688190b30d285cd7aa0d82 completed Feb. 28, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3c8b7274881908e13da8bb2c83858 completed March 1, 2026, 5:03 a.m.
NEDg Description generation batch_69a3c93ce2308190b2df5c939691a2ce completed March 1, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_69a3ca020b7081909b54e311c173ef21 completed March 1, 2026, 5:09 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.