Triple
T11310893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | siSwati |
E267830
|
entity |
| Predicate | countryStatusInSouthAfrica |
P33447
|
FINISHED |
| Object | official language |
—
|
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: official language | Statement: [siSwati, countryStatusInSouthAfrica, official language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryStatusInSouthAfrica Context triple: [siSwati, countryStatusInSouthAfrica, official language]
-
A.
countryStatusInZimbabwe
Indicates the legal or diplomatic status that an entity holds within or in relation to Zimbabwe.
-
B.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
C.
countrySpecificStatus
chosen
Indicates a status or condition that is defined or applied specifically in the context of a particular country.
-
D.
continentStatus
Indicates the status or condition assigned to a continent, such as its current state, classification, or role within a given context.
-
E.
chartPositionSouthAfrica
Indicates the position or ranking something holds on a chart or listing specifically within South Africa.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787aa31888190860eecaa80da5b20 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.