Triple

T20395330
Position Surface form Disambiguated ID Type / Status
Subject Hanis Coos E500187 entity
Predicate hasDistinctLanguage P9366 FINISHED
Object Hanis 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: Hanis language | Statement: [Hanis Coos, hasDistinctLanguage, Hanis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanis language
Context triple: [Hanis Coos, hasDistinctLanguage, Hanis language]
  • A. Hanis language chosen
    The Hanis language is an endangered Native American language traditionally spoken by the Coos people of the southern Oregon coast.
  • B. Hani language
    The Hani language is a Tibeto-Burman language spoken primarily by the Hani people in southwestern China and neighboring regions of Southeast Asia.
  • C. Huarijio language
    The Huarijio language is an indigenous Uto-Aztecan language spoken by the Huarijio people of northwestern Mexico, primarily in the Sierra Madre Occidental region.
  • D. Hu language
    Hu language is a variety of Wu Chinese spoken primarily in and around Shanghai, known for its distinct phonology and vocabulary compared to Standard Mandarin.
  • E. Hamer-Banna language
    The Hamer-Banna language is an Omotic language spoken primarily by the Hamer and Banna ethnic groups in southwestern Ethiopia.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67912d7948190ac2fda8ce95e5c70 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.