Triple

T57643
Position Surface form Disambiguated ID Type / Status
Subject Ecuador E1141 entity
Predicate recognizedLanguage P238 FINISHED
Object Kichwa
Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
 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: Kichwa | Statement: [Ecuador, recognizedLanguage, Kichwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kichwa
Context triple: [Ecuador, recognizedLanguage, Kichwa]
  • A. Aymara
    Aymara is an indigenous language spoken primarily by the Aymara people of the central Andes in countries such as Bolivia, Peru, and Chile.
  • B. Tebu
    Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • C. Sranan Tongo
    Sranan Tongo is an English- and Dutch-influenced creole language originating in Suriname, widely used as a lingua franca among its diverse ethnic communities.
  • D. Namba
    Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
  • E. Culebra
    Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
  • 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: Kichwa
Triple: [Ecuador, recognizedLanguage, Kichwa]
Generated description
Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kichwa
Target entity description: Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • A. Aymara
    Aymara is an indigenous language spoken primarily by the Aymara people of the central Andes in countries such as Bolivia, Peru, and Chile.
  • B. Tebu
    Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • C. Sranan Tongo
    Sranan Tongo is an English- and Dutch-influenced creole language originating in Suriname, widely used as a lingua franca among its diverse ethnic communities.
  • D. Namba
    Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
  • E. Culebra
    Culebra is a small Caribbean island municipality of Puerto Rico known for its pristine beaches, clear waters, and protected wildlife refuges.
  • F. None of above. chosen

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_69a248adc5b48190aa8db9fb092fb28a completed Feb. 28, 2026, 1:45 a.m.
NER Named-entity recognition batch_69a24b1bf2c081908f20e13939b713ff completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a25ab7ec3881909356c659f4664fb8 completed Feb. 28, 2026, 3:02 a.m.
NEDg Description generation batch_69a25ba79ab881909fa4570aa2acf402 completed Feb. 28, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_69a25c28192081909853f2833f1472ef completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 1:50 a.m.