Triple
T4533118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Vizier Sinan Pasha |
E106343
|
entity |
| Predicate | thirdTermAsGrandVizierStart |
P57312
|
FINISHED |
| Object | 1593 |
—
|
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: 1593 | Statement: [Grand Vizier Sinan Pasha, thirdTermAsGrandVizierStart, 1593]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdTermAsGrandVizierStart Context triple: [Grand Vizier Sinan Pasha, thirdTermAsGrandVizierStart, 1593]
-
A.
successorAsGrandVizier
Indicates that one entity became the next Grand Vizier following another entity in that office.
-
B.
thirdMonarch
Indicates that the subject is the third monarch in a succession or lineage relative to a specified realm or dynasty.
-
C.
hasThirdTerm
Indicates that an entity is associated with or includes a specific third term in an ordered sequence or grouping.
-
D.
thirdConsul
Indicates that an entity holds the position or role of the third consul in a specified governing body or context.
-
E.
thirdSecretaryGeneral
Indicates that the subject served as the third person to hold the position of Secretary-General in a given organization or context.
- 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_69bd43f3d6e08190a91824f833d51bbe |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57a08ec4819091b84d53d7b564a7 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:04 p.m.