Triple
T14965396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European bourgeoisie |
E373176
|
entity |
| Predicate | hasTypicalOccupation |
P116875
|
FINISHED |
| Object | industrialist |
—
|
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: industrialist | Statement: [European bourgeoisie, hasTypicalOccupation, industrialist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalOccupation Context triple: [European bourgeoisie, hasTypicalOccupation, industrialist]
-
A.
holderIsOccupation
Indicates that the holder entity has the specified occupation or job role.
-
B.
isOccupationalFormOf
Indicates that one occupation is a specific form, variant, or specialization of another, more general occupation.
-
C.
hasOccupationFocus
Indicates that an entity’s occupation is primarily centered on, or specialized in, a particular field, role, or area of activity.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
hasOccupationDuringStory
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e2fdcc8190bffe603db3388736 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:47 a.m.