Triple
T11469350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buga language |
E271860
|
entity |
| Predicate | riskOfLanguageShift |
P99457
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Buga language, riskOfLanguageShift, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskOfLanguageShift Context triple: [Buga language, riskOfLanguageShift, high]
-
A.
heritageLanguageShift
Indicates a change over time in which a community or individual moves away from using their ancestral or heritage language toward another dominant language.
-
B.
causeOfLanguageShift
Indicates a factor or event that leads to a change from one dominant language or linguistic pattern to another within a community or population.
-
C.
languageShift
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.
-
D.
languageShiftPressureFrom
Indicates pressure exerted by one entity that causes or encourages another entity to shift away from its current language toward a different language.
-
E.
languageAffected
Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
- F. None of above. chosen
Provenance (4 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d82949e3688190b024a4980666c94f |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d8279925e4819089210611c0d8e61a |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:35 p.m.