Triple
T32589606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dauphine |
E833028
|
entity |
| Predicate | rankRelativeToPrincesses |
P50407
|
FINISHED |
| Object | above other princesses of the blood |
—
|
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: above other princesses of the blood | Statement: [Dauphine, rankRelativeToPrincesses, above other princesses of the blood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankRelativeToPrincesses Context triple: [Dauphine, rankRelativeToPrincesses, above other princesses of the blood]
-
A.
princessOf
Indicates that one entity holds the royal title or role of princess in relation to another entity, typically a realm, family, or sovereign.
-
B.
rankInPrincelyOrder
chosen
Indicates the position or level an entity holds within a specified princely order or hierarchy.
-
C.
relationshipToPrincess
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
D.
notableCrownPrincess
Indicates that the person holds or held the title of crown princess and is distinguished or noteworthy in that role.
-
E.
royalMistressOf
Indicates that one person is the (typically unofficial) romantic or sexual partner of a royal figure, such as a king or prince.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c67138e8819099aa4ded014143ba |
completed | May 3, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:04 a.m.