Triple
T21938795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punjabi diaspora |
E541760
|
entity |
| Predicate | hasLanguageShiftTrend |
P99457
|
FINISHED |
| Object | bilingualism |
—
|
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: bilingualism | Statement: [Punjabi diaspora, hasLanguageShiftTrend, bilingualism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageShiftTrend Context triple: [Punjabi diaspora, hasLanguageShiftTrend, bilingualism]
-
A.
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.
-
B.
riskOfLanguageShift
chosen
Indicates that there is a likelihood or tendency for one language to be replaced or significantly reduced in use by another within a given community or context.
-
C.
languageUseTrend
Indicates how the use or prevalence of a particular language changes over time within a given population or context.
-
D.
hasCulturalShift
Indicates a change in the prevailing beliefs, values, norms, or practices within a group, organization, or society over time.
-
E.
hasTonalityShift
Indicates a change in the tonal quality, mood, or key within a piece or segment, marking a shift from one tonality to another.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1241f582c81909a244419cec38b19 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.