Triple

T19817793
Position Surface form Disambiguated ID Type / Status
Subject Yeniseian languages E476104 entity
Predicate extinctLanguages P11825 FINISHED
Object Arin 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: Arin language | Statement: [Yeniseian languages, extinctLanguages, Arin language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arin language
Context triple: [Yeniseian languages, extinctLanguages, Arin language]
  • A. Arin language chosen
    The Arin language is an extinct Yeniseian language once spoken along the Yenisei River in central Siberia.
  • B. Ahirani language
    Ahirani language is an Indo-Aryan language spoken primarily in the Khandesh region of Maharashtra, India, known for its close relation to Marathi and distinct regional dialectal features.
  • C. Aringa language
    The Aringa language is a Central Sudanic language spoken primarily by the Aringa people in northwestern Uganda.
  • D. Aringa language
    The Aringa language is a Western Nilotic language spoken primarily by the Aringa people in northwestern Uganda.
  • E. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e654fac7b481909a19ae0d608e01d9 completed April 20, 2026, 4:31 p.m.
Created at: April 10, 2026, 1:50 p.m.