Triple
T28304839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise de Kérouaille, Duchess of Portsmouth |
E713810
|
entity |
| Predicate | mistressOf |
P86632
|
FINISHED |
| Object | Charles II of England |
—
|
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: Charles II of England | Statement: [Louise de Kérouaille, Duchess of Portsmouth, mistressOf, Charles II of England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mistressOf Context triple: [Louise de Kérouaille, Duchess of Portsmouth, mistressOf, Charles II of England]
-
A.
hadMistress
Indicates that a person maintained an extramarital or unofficial romantic/sexual relationship with another person.
-
B.
relationshipToMistressPage
Indicates a person’s specific relational role or connection to Mistress Page.
-
C.
royalMistressOf
chosen
Indicates that one person is the (typically unofficial) romantic or sexual partner of a royal figure, such as a king or prince.
-
D.
chiefMistressOf
Indicates that one person is the primary or most important mistress (non-marital romantic or sexual partner) of another person.
-
E.
isMasterOf
Indicates that one entity holds a position of control, authority, or ownership over another entity.
- 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_69efb524ab688190a1ce7ee7c9520932 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f644b5d814819098c20ea8f6051ce8 |
completed | May 2, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:37 p.m.