Triple
T13884584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nonnberg Abbey |
E333805
|
entity |
| Predicate | hasVocation |
P12782
|
FINISHED |
| Object | monastic vocation |
—
|
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: monastic vocation | Statement: [Nonnberg Abbey, hasVocation, monastic vocation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocation Context triple: [Nonnberg Abbey, hasVocation, monastic vocation]
-
A.
vocationType
chosen
Indicates the specific kind or category of occupation, profession, or calling associated with an entity.
-
B.
hasProfessionTrait
Indicates that an entity possesses a particular characteristic, quality, or attribute specifically related to their profession or occupational role.
-
C.
targetVocation
Indicates that an entity is the intended or designated profession, occupation, or calling for another entity.
-
D.
vocationFocus
Indicates that an entity’s primary vocational attention, effort, or specialization is directed toward another entity or subject.
-
E.
hasWorkProgram
Indicates that an entity offers, participates in, or is associated with a specific work-related program or scheme.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:15 p.m.