Triple
T7139334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Sheppard |
E166400
|
entity |
| Predicate | apprenticeship |
P22559
|
FINISHED |
| Object | carpenter |
—
|
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: carpenter | Statement: [Jack Sheppard, apprenticeship, carpenter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apprenticeship Context triple: [Jack Sheppard, apprenticeship, carpenter]
-
A.
offersApprenticeshipTraining
Indicates that one entity provides apprenticeship-based training opportunities or programs to another entity.
-
B.
internship
Indicates that one entity is engaged in a temporary, often educational work placement or training position with another entity, typically to gain practical experience.
-
C.
trainedAs
chosen
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
D.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
developmentAcademy
Indicates a relationship where an academy is responsible for or involved in the development, training, or educational advancement of individuals or groups.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e694cc3c81908b0d54c2496a0722 |
completed | March 27, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:45 p.m.