Triple
T20380511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | von Below |
E497812
|
entity |
| Predicate | hasTypicalOccupationAmongBearers |
P116875
|
FINISHED |
| Object | military officer |
—
|
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: military officer | Statement: [von Below, hasTypicalOccupationAmongBearers, military officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalOccupationAmongBearers Context triple: [von Below, hasTypicalOccupationAmongBearers, military officer]
-
A.
commonProfessionAmongBearers
Indicates that multiple entities sharing a given attribute (such as a name or title) are frequently associated with the same profession.
-
B.
hasTypicalOccupation
chosen
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
C.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678b026e081909541e545886c8380 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.