Triple
T19573112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Health Sciences |
E489772
|
entity |
| Predicate | offersCareerPreparationFor |
P33629
|
FINISHED |
| Object | healthcare careers |
—
|
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: healthcare careers | Statement: [School of Health Sciences, offersCareerPreparationFor, healthcare careers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersCareerPreparationFor Context triple: [School of Health Sciences, offersCareerPreparationFor, healthcare careers]
-
A.
offersApprenticeshipTraining
chosen
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
-
B.
helpsLaunchCareerOf
Indicates that one entity plays a significant role in starting, advancing, or establishing the professional career of another entity.
-
C.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
-
D.
studCareer
Indicates that a student is pursuing or associated with a particular academic or professional career path.
-
E.
studCareerAt
Indicates that a student pursued or developed their academic or professional career at a particular institution or organization.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402228488190b5649d4bbd34d019 |
completed | April 20, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:42 p.m.