Triple
T24186777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton S. Hershey |
E599577
|
entity |
| Predicate | apprenticedAs |
P149666
|
FINISHED |
| Object | confectioner |
—
|
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: confectioner | Statement: [Milton S. Hershey, apprenticedAs, confectioner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apprenticedAs Context triple: [Milton S. Hershey, apprenticedAs, confectioner]
-
A.
apprenticeshipOccupation
chosen
Indicates that one entity serves as the occupation or trade in which another entity is undergoing or has undergone apprenticeship training.
-
B.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
C.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
-
D.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
apprenticeshipLocation
Indicates the place or institution where an apprenticeship is carried out or hosted.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:35 p.m.