Triple

T19817788
Position Surface form Disambiguated ID Type / Status
Subject Yeniseian languages E476104 entity
Predicate hasRepresentativeLanguage P53040 FINISHED
Object Ket 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: Ket language | Statement: [Yeniseian languages, hasRepresentativeLanguage, Ket language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ket language
Context triple: [Yeniseian languages, hasRepresentativeLanguage, Ket language]
  • A. Ket language chosen
    The Ket language is a critically endangered Yeniseian language of central Siberia, spoken by the Ket people along the Yenisei River and notable for its complex morphology and debated genetic links to Na-Dene languages of North America.
  • B. Pear language
    Pear language is an Austroasiatic language of the Pearic branch spoken by the Pear people of Cambodia and considered highly endangered.
  • C. Keo language
    The Keo language is an Austronesian language spoken by the Keo people on Flores Island in Indonesia.
  • D. Kryts language
    The Kryts language is a Northeast Caucasian language spoken by the Kryts people in parts of Azerbaijan.
  • E. Keka language
    Keka is an Austronesian language spoken on Rote Island in Indonesia, belonging to the Rote subgroup of languages.
  • 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.