Triple
T6973411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Hani Baragwanath Hospital |
E161651
|
entity |
| Predicate | trainingSiteFor |
P40765
|
FINISHED |
| Object | medical students |
—
|
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: medical students | Statement: [Chris Hani Baragwanath Hospital, trainingSiteFor, medical students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingSiteFor Context triple: [Chris Hani Baragwanath Hospital, trainingSiteFor, medical students]
-
A.
trainingLocationType
Indicates the type or category of place where a training activity occurs.
-
B.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
C.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
D.
trainingSupport
Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
-
E.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db3aad108190b19df2d21f5ce168 |
completed | March 27, 2026, 7:32 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.