Triple

T18739308
Position Surface form Disambiguated ID Type / Status
Subject Dani people E458248 entity
Predicate language P15 FINISHED
Object Dani language NE NERFINISHED

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: Dani language | Statement: [Dani people, language, Dani language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dani language
Context triple: [Dani people, language, Dani language]
  • A. Dani languages chosen
    The Dani languages are a group of closely related Papuan languages spoken primarily in the central highlands of Papua (Indonesian New Guinea), known for their large speaker populations and cultural significance among the Dani peoples.
  • B. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • C. Dimasa language
    Dimasa is a Tibeto-Burman language spoken primarily by the Dimasa people in the Indian states of Assam and Nagaland.
  • D. Tyap language
    Tyap language is a Plateau language of the Niger-Congo family spoken predominantly by the Atyap people in southern Kaduna State, Nigeria.
  • E. Mari language
    The Mari language is a Uralic language spoken primarily by the Mari people in the Mari El Republic and surrounding regions of Russia, known for its distinct dialects and rich oral tradition.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5768ca990819098102f8522ce401f completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.