Triple

T38214485
Position Surface form Disambiguated ID Type / Status
Subject Kangjia people E1010645 entity
Predicate linguisticEndangermentCause P45185 FINISHED
Object shift to Chinese language LITERAL FINISHED

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: shift to Chinese language | Statement: [Kangjia people, linguisticEndangermentCause, shift to Chinese language]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: linguisticEndangermentCause
Context triple: [Kangjia people, linguisticEndangermentCause, shift to Chinese language]
  • A. languageEndangermentFactors chosen
    Indicates the various social, political, economic, and cultural conditions that contribute to a language becoming vulnerable, endangered, or extinct.
  • B. endangeredLanguage
    Indicates that a language is at risk of falling out of use and potentially becoming extinct due to having too few active speakers or insufficient intergenerational transmission.
  • C. extinctionOfLanguage
    Indicates the event or process by which a language ceases to be spoken or used by any living community.
  • D. languageDeathCause
    Indicates the cause or factor responsible for the extinction or disappearance of a language.
  • E. linguisticIsolation
    Indicates a condition where an entity is separated from others in terms of language, lacking shared or effective linguistic communication.
  • F. None of above.

Provenance (3 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_69f76dcdc7708190a5f1751d53f40ffe completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcc42cbac48190b8d3e4c9ce140838 completed May 7, 2026, 4:56 p.m.
PD Predicate disambiguation batch_69fcb0fc69c88190800453eb57a7e62c completed May 7, 2026, 3:34 p.m.
Created at: May 3, 2026, 4:30 p.m.