Triple
T38433831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Beatrice d’Este |
E903879
|
entity |
| Predicate | successorAsPrincessOfCarrara |
P203064
|
FINISHED |
| Object | Francis IV, Duke of Modena |
—
|
NE NERFINISHED |
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: Francis IV, Duke of Modena | Statement: [Maria Beatrice d’Este, successorAsPrincessOfCarrara, Francis IV, Duke of Modena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorAsPrincessOfCarrara Context triple: [Maria Beatrice d’Este, successorAsPrincessOfCarrara, Francis IV, Duke of Modena]
-
A.
successorAsPrincessOfTaranto
Indicates that one entity became the next holder of the title Princess of Taranto after another entity.
-
B.
successorAsDuchessOfMassa
Indicates that one person became the next Duchess of Massa following another in the line of succession.
-
C.
successorAsGrandDukeOfTuscany
Indicates the person who directly followed another as the Grand Duke of Tuscany in the line of succession.
-
D.
successorAsKingOfNaples
Indicates that one person became the next king of Naples following another person’s reign.
-
E.
successorAsQueenOfAragon
Indicates that one person became the next reigning queen of Aragon after another person.
- 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_69f76e6a2024819081aa04f4932f89d2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0119132e848190820a688d139fbf75 |
completed | May 10, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_6a01188dfdec8190b7f675264a281733 |
completed | May 10, 2026, 11:45 p.m. |
| PDg | Predicate description generation | batch_6a0119127ca481909e921e7d95716b00 |
completed | May 10, 2026, 11:47 p.m. |
Created at: May 3, 2026, 4:31 p.m.