Triple

T6469592
Position Surface form Disambiguated ID Type / Status
Subject Tupian E142313 entity
Predicate wellKnownLanguage P42338 FINISHED
Object Juruna language
The Juruna language is an indigenous Tupian language spoken by the Juruna (Yudjá) people of the Xingu region in Brazil.
 E597887 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: Juruna language | Statement: [Tupian, wellKnownLanguage, Juruna language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Juruna language
Context triple: [Tupian, wellKnownLanguage, Juruna language]
  • A. Warao language
    The Warao language is an indigenous language isolate spoken by the Warao people of northeastern Venezuela and nearby regions, particularly in the Orinoco Delta.
  • B. Jarawa language
    The Jarawa language is an endangered Ongan language spoken by the indigenous Jarawa people of the Andaman Islands in India.
  • C. Terena language
    The Terena language is an Arawakan indigenous language spoken primarily by the Terena people of Brazil’s Mato Grosso do Sul region.
  • D. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • E. Tapirapé language
    Tapirapé is an indigenous Tupian language spoken by the Tapirapé people of Brazil, known for its complex morphology and endangered status.
  • 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: Juruna language
Triple: [Tupian, wellKnownLanguage, Juruna language]
Generated description
The Juruna language is an indigenous Tupian language spoken by the Juruna (Yudjá) people of the Xingu region in Brazil.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Juruna language
Target entity description: The Juruna language is an indigenous Tupian language spoken by the Juruna (Yudjá) people of the Xingu region in Brazil.
  • A. Warao language
    The Warao language is an indigenous language isolate spoken by the Warao people of northeastern Venezuela and nearby regions, particularly in the Orinoco Delta.
  • B. Jarawa language
    The Jarawa language is an endangered Ongan language spoken by the indigenous Jarawa people of the Andaman Islands in India.
  • C. Terena language
    The Terena language is an Arawakan indigenous language spoken primarily by the Terena people of Brazil’s Mato Grosso do Sul region.
  • D. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • E. Tapirapé language
    Tapirapé is an indigenous Tupian language spoken by the Tapirapé people of Brazil, known for its complex morphology and endangered status.
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06a16272c81909313455002cd884d completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c66382f9ac81908d9cb444ab596d04 completed March 27, 2026, 11:01 a.m.
NEDg Description generation batch_69c6646fa43c819085338458113e5bf9 completed March 27, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69c664d154dc81908d48056d272c56fa completed March 27, 2026, 11:06 a.m.
Created at: March 22, 2026, 4:50 p.m.