Triple
T9960500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilian Chouerite Order |
E195554
|
entity |
| Predicate | vocationFocus |
P91665
|
FINISHED |
| Object | monastic vocations |
—
|
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 vocations | Statement: [Basilian Chouerite Order, vocationFocus, monastic vocations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocationFocus Context triple: [Basilian Chouerite Order, vocationFocus, monastic vocations]
-
A.
vocationType
Indicates the specific kind or category of occupation, profession, or calling associated with an entity.
-
B.
dedicatedToOccupation
Indicates that an entity is committed or devoted to performing or pursuing a particular occupation or professional role.
-
C.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
- F. None of above. chosen
Provenance (4 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6d219c48190b2084b0eb07ae125 |
completed | April 2, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9ae19c819099fb3635e57c79be |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:47 p.m.