Triple

T21053745
Position Surface form Disambiguated ID Type / Status
Subject Doe language E518653 entity
Predicate neighboringLanguage P16383 FINISHED
Object Kami 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: Kami language | Statement: [Doe language, neighboringLanguage, Kami language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kami language
Context triple: [Doe language, neighboringLanguage, Kami language]
  • A. Kami language chosen
    The Kami language is a Bantu language spoken along Tanzania’s northeastern coast, belonging to the Northeast Coast Bantu subgroup.
  • B. Unami language
    The Unami language is an Eastern Algonquian Native American language traditionally spoken by the Lenape (Delaware) people in the mid-Atlantic region of the United States.
  • C. Kam language
    Kam is a Tai–Kadai language spoken primarily by the Kam (Dong) people of southern China, known for its rich tonal system and distinct northern and southern dialects.
  • D. Kamayurá language
    The Kamayurá language is an indigenous Tupian language spoken by the Kamayurá people of Brazil’s Upper Xingu region in the Amazon.
  • E. Kitanemuk language
    The Kitanemuk language is an extinct Uto-Aztecan language once spoken by the Kitanemuk people of Southern California.
  • 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_69e0b5053ac48190921529544959e906 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fd7e087c81908712ddc63e8b1e6c completed April 21, 2026, 4:30 a.m.
Created at: April 16, 2026, 2:36 p.m.