Triple
T2820769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Cape Provincial Government |
E54801
|
entity |
| Predicate | languagePolicyRegion |
P43520
|
FINISHED |
| Object | Afrikaans |
—
|
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: Afrikaans | Statement: [Western Cape Provincial Government, languagePolicyRegion, Afrikaans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languagePolicyRegion Context triple: [Western Cape Provincial Government, languagePolicyRegion, Afrikaans]
-
A.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
B.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
languagePolicyIssue
Indicates that there is a problem, conflict, or concern related to rules or practices governing language use.
-
D.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
-
E.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abdf15b7288190a03d1193cc0544a6 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd08f2f481908c3da8a9c7a00552 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdf13d2b8819097b8edaaea90dbe2 |
completed | March 7, 2026, 8:17 a.m. |
Created at: March 6, 2026, 9:59 p.m.