Triple
T32855132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court of Louis XVI of France |
E840355
|
entity |
| Predicate | hasSpouseOfMonarchPresent |
P194528
|
FINISHED |
| Object | Marie Antoinette |
—
|
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: Marie Antoinette | Statement: [Court of Louis XVI of France, hasSpouseOfMonarchPresent, Marie Antoinette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseOfMonarchPresent Context triple: [Court of Louis XVI of France, hasSpouseOfMonarchPresent, Marie Antoinette]
-
A.
spouseIsMonarchOf
Indicates that a person's spouse holds the position of monarch (ruler) of a specified country or territory.
-
B.
spouseServedMonarch
Indicates that the spouse of a person held a position of service or duty to a monarch.
-
C.
spouseOfHeirToThrone
Indicates that one person is the married partner of an individual who is the heir to a throne.
-
D.
hasNotableRoyalConsort
Indicates that a person has a royal consort who is particularly notable or distinguished in some recognized way.
-
E.
marriedToFutureMonarch
Indicates that one person is married to another person who will become a monarch in the future.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
| PDg | Predicate description generation | batch_69fd783e9e5c819087dec7fefa03700d |
completed | May 8, 2026, 5:44 a.m. |
Created at: May 1, 2026, 1:17 a.m.