Triple
T461921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Protestant Theological Faculty |
E7356
|
entity |
| Predicate | trainsForOccupation |
P14268
|
FINISHED |
| Object | clergy |
—
|
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: clergy | Statement: [Protestant Theological Faculty, trainsForOccupation, clergy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsForOccupation Context triple: [Protestant Theological Faculty, trainsForOccupation, clergy]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
C.
usedForRailwayTimetables
Indicates that something is employed in the creation, organization, or presentation of railway timetables.
-
D.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
E.
rollingStockOperator
Indicates that an entity operates or manages rolling stock, such as trains or rail vehicles, in a railway system.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede8eac081908dffade6a5e7950b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef06d2fc8190b379d575215a8518 |
completed | Feb. 28, 2026, 1:35 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.