Triple
T26999607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LLB programme (University of the Witwatersrand) |
E680068
|
entity |
| Predicate | aimsToPrepareFor |
P2534
|
FINISHED |
| Object | legal practice |
—
|
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: legal practice | Statement: [LLB programme (University of the Witwatersrand), aimsToPrepareFor, legal practice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimsToPrepareFor Context triple: [LLB programme (University of the Witwatersrand), aimsToPrepareFor, legal practice]
-
A.
preparesFor
chosen
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
-
B.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
C.
preparedFor
Indicates that one entity has been made ready, equipped, or arranged in anticipation of use by or in connection with another entity.
-
D.
aimsToDevelop
Indicates an entity’s intention or effort to create, improve, or bring about another entity, outcome, or capability.
-
E.
competitionLevelPreparedFor
Indicates the degree or intensity of competition that an entity is ready or equipped to face.
- 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621cbc48881908d104c648c91c715 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 6:56 a.m.