Triple

T10880230
Position Surface form Disambiguated ID Type / Status
Subject Tupian languages E256900 entity
Predicate includesLanguage P2177 FINISHED
Object Mundurukú language E596811 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: Mundurukú language | Statement: [Tupian languages, includesLanguage, Mundurukú language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mundurukú language
Context triple: [Tupian languages, includesLanguage, Mundurukú language]
  • A. Munduruku language chosen
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • B. Juruna language
    The Juruna language is an indigenous Tupian language spoken by the Juruna (Yudjá) people of the Xingu region in Brazil.
  • C. 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.
  • D. Tapirapé language
    Tapirapé is an indigenous Tupian language spoken by the Tapirapé people of Brazil, known for its complex morphology and endangered status.
  • E. Terena language
    The Terena language is an Arawakan indigenous language spoken primarily by the Terena people of Brazil’s Mato Grosso do Sul region.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751b031a88190b1182dfc1f520264 completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154d8f9b881908025acc6ff1beb9f completed April 16, 2026, 9:30 p.m.
Created at: April 8, 2026, 9:21 p.m.