Triple
T34198891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Promotion of Bantu Self-Government Act |
E877315
|
entity |
| Predicate | legalCategoryUsed |
P76736
|
FINISHED |
| Object | Bantu |
—
|
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: Bantu | Statement: [Promotion of Bantu Self-Government Act, legalCategoryUsed, Bantu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalCategoryUsed Context triple: [Promotion of Bantu Self-Government Act, legalCategoryUsed, Bantu]
-
A.
juridicalCategory
chosen
Indicates the legal classification or status under which an entity or relationship is formally recognized in a juridical system.
-
B.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
C.
legalFeature
Indicates that something possesses a specific legal characteristic, status, or attribute relevant to laws or regulations.
-
D.
legalTermUsedFrom
Indicates that a particular legal term has been in official or recognized use starting from a specified point in time.
-
E.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
- 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff4fc6077c8190b8fd9b43fcfde986 |
completed | May 9, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69ff4e61fb648190a72f7918961ece9c |
completed | May 9, 2026, 3:10 p.m. |
Created at: May 1, 2026, 1:55 a.m.