Triple
T26731817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stefano Casiraghi |
E673994
|
entity |
| Predicate | startTimeOfMarriageWithPrincessCarolineOfMonaco |
P181634
|
FINISHED |
| Object | 1983-12-29 |
—
|
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: 1983-12-29 | Statement: [Stefano Casiraghi, startTimeOfMarriageWithPrincessCarolineOfMonaco, 1983-12-29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfMarriageWithPrincessCarolineOfMonaco Context triple: [Stefano Casiraghi, startTimeOfMarriageWithPrincessCarolineOfMonaco, 1983-12-29]
-
A.
endTimeOfMarriageWithPrincessCarolineOfMonaco
Indicates the date and time when a person’s marriage to Princess Caroline of Monaco ended.
-
B.
placeOfMarriage (to Princess Caroline of Monaco)
Indicates the location where the marriage to Princess Caroline of Monaco took place.
-
C.
marriageToPrinceStart
Indicates the point in time when an individual begins being married to a prince.
-
D.
marriageStartDateWithRobertCarr
Indicates the date on which an entity’s marriage to Robert Carr began.
-
E.
startTime (marriage to Princess Irene of the Netherlands)
Indicates the date and time when the marriage to Princess Irene of the Netherlands began.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: April 27, 2026, 3:45 a.m.