Triple
T13450439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Assyria |
E320593
|
entity |
| Predicate | exercisedControlThrough |
P6502
|
FINISHED |
| Object | provincial governors |
—
|
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: provincial governors | Statement: [King of Assyria, exercisedControlThrough, provincial governors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exercisedControlThrough Context triple: [King of Assyria, exercisedControlThrough, provincial governors]
-
A.
exercisedPowerOver
chosen
Indicates that one entity exerted control, influence, or authority over another entity.
-
B.
usedToControl
Indicates that one entity employed another as a means or tool to exercise control or regulation over something.
-
C.
exercisedPowerFrom
Indicates that one entity exerted authority, control, or influence originating from a particular source, position, or location over another entity or context.
-
D.
controlledIn
Indicates that one entity exercised control, authority, or governance over another entity within a specific context or domain.
-
E.
affectedControlOf
Indicates that one entity has influenced, altered, or impacted the degree of control another entity has over something.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaef973b08190a3d7fe1c2a913cff |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.