Triple
T17942147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midhat Pasha |
E448611
|
entity |
| Predicate | termAsGrandVizierEnd |
P129816
|
FINISHED |
| Object | 1872 |
—
|
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: 1872 | Statement: [Midhat Pasha, termAsGrandVizierEnd, 1872]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termAsGrandVizierEnd Context triple: [Midhat Pasha, termAsGrandVizierEnd, 1872]
-
A.
firstTermAsGrandVizierEnd
Indicates the date or point in time when an entity’s initial tenure as Grand Vizier came to an end.
-
B.
thirdTermAsGrandVizierEnd
Indicates the time or event marking the end of a person's third term serving as Grand Vizier.
-
C.
termCountAsGrandVizier
Indicates the number of distinct terms an individual has served in the role of Grand Vizier.
-
D.
thirdTermAsGrandVizierStart
Indicates the date or point in time when an entity begins serving a third term in the role of Grand Vizier.
-
E.
secondTermAsGrandVizierStart
Indicates the date or point in time when an individual’s second term serving as Grand Vizier begins.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad96a9008190867fac99588c43cf |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:21 a.m.