Triple

T6725807
Position Surface form Disambiguated ID Type / Status
Subject Rarámuri people E153513 entity
Predicate language P15 FINISHED
Object Rarámuri language E159279 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: Rarámuri language | Statement: [Rarámuri people, language, Rarámuri language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rarámuri language
Context triple: [Rarámuri people, language, Rarámuri language]
  • A. Rarámuri language chosen
    The Rarámuri language is an indigenous Uto-Aztecan language spoken by the Tarahumara (Rarámuri) people of northern Mexico.
  • B. Mampruli language
    Mampruli is a Gur language spoken primarily by the Mamprusi people in northern Ghana and parts of neighboring West African countries.
  • C. Patamona language
    The Patamona language is an indigenous Cariban language spoken by the Patamona people of the Guiana Highlands in Guyana and northern Brazil.
  • D. Munduruku language
    The Munduruku language is an indigenous Tupian language spoken by the Munduruku people of the Amazon region in Brazil.
  • E. Mararit language
    The Mararit language is a lesser-known Nilo-Saharan language spoken by the Mararit people in parts of Chad and Sudan.
  • 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_69c6880afb988190ad88011b48ecfcba completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d15131f08190aba6c00943c51331 completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700a5428c81908d4484c3e3734076 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:08 p.m.