Triple
T1079162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ǀXam |
E23906
|
entity |
| Predicate | causeOfLanguageShift |
P23674
|
FINISHED |
| Object | colonial dispossession and assimilation policies |
—
|
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: colonial dispossession and assimilation policies | Statement: [ǀXam, causeOfLanguageShift, colonial dispossession and assimilation policies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfLanguageShift Context triple: [ǀXam, causeOfLanguageShift, colonial dispossession and assimilation policies]
-
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.
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.
-
C.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
D.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
E.
influencedLanguageFamily
Indicates that one language family has had a significant impact on the development, structure, or usage of another language family.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b943b41481909b24050ca7e78971 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.