Triple
T21697870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Sisterhood of Martha and Mary |
E535572
|
entity |
| Predicate | primaryVocation |
P12782
|
FINISHED |
| Object | nursing |
—
|
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: nursing | Statement: [Christian Sisterhood of Martha and Mary, primaryVocation, nursing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryVocation Context triple: [Christian Sisterhood of Martha and Mary, primaryVocation, nursing]
-
A.
primaryWork
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
-
B.
vocationType
chosen
Indicates the specific kind or category of occupation, profession, or calling associated with an entity.
-
C.
vocationFocus
Indicates that an entity’s primary vocational attention, effort, or specialization is directed toward another entity or subject.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
natureOfOccupation
Indicates the type or character of a person's occupation, describing what kind of work or role it is rather than who performs it.
- 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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef9b7caca0819083d839b276ae015b |
completed | April 27, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:45 p.m.