Triple
T21431783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrietta Wilson |
E528704
|
entity |
| Predicate | professionallyTrainedAs |
P22559
|
FINISHED |
| Object | paramedic |
—
|
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: paramedic | Statement: [Henrietta Wilson, professionallyTrainedAs, paramedic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionallyTrainedAs Context triple: [Henrietta Wilson, professionallyTrainedAs, paramedic]
-
A.
trainedAs
chosen
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
B.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
C.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
D.
isProfessionalGraduateInstitution
Indicates that an institution functions as a professional-level graduate school, offering advanced degrees or training beyond the undergraduate level.
-
E.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3ec70f08190b84c4f747cfb290f |
completed | April 22, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:49 p.m.