Triple

T17630845
Position Surface form Disambiguated ID Type / Status
Subject Xianbei language E429970 entity
Predicate languageShiftOutcome P4292 FINISHED
Object sinicization of Xianbei elites 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: sinicization of Xianbei elites | Statement: [Xianbei language, languageShiftOutcome, sinicization of Xianbei elites]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageShiftOutcome
Context triple: [Xianbei language, languageShiftOutcome, sinicization of Xianbei elites]
  • A. languageShift chosen
    Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
  • B. languageAffected
    Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
  • C. languageShiftPressureFrom
    Indicates pressure exerted by one entity that causes or encourages another entity to shift away from its current language toward a different language.
  • D. languageUse
    Indicates the language or languages an entity uses for communication, expression, or interaction.
  • E. languageOutcome
    Indicates the resulting language or linguistic state that emerges from a given process, action, or interaction.
  • 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46dc192dc8190854f1fe5d5ed696a completed April 19, 2026, 5:53 a.m.
PD Predicate disambiguation batch_69e3cddc87188190ac2f049b86038676 completed April 18, 2026, 6:30 p.m.
Created at: April 10, 2026, 5:52 a.m.