Triple
T1037554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame de Montespan |
E22398
|
entity |
| Predicate | numberOfChildrenWithLouisXIV |
P24222
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Madame de Montespan, numberOfChildrenWithLouisXIV, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChildrenWithLouisXIV Context triple: [Madame de Montespan, numberOfChildrenWithLouisXIV, 7]
-
A.
successorInFranceClaim
Indicates that one entity is recognized or asserted as the successor to another entity specifically in the context of a claim related to France.
-
B.
hasNumberOfRulers
Indicates the quantity of rulers associated with or governing a given entity.
-
C.
secondMonarch
Indicates that one entity is the second monarch (in chronological order of reign) in relation to another specified realm, dynasty, or succession context.
-
D.
numberOfDeputiesSecondEstate
Indicates the total count of deputies or representatives belonging to the Second Estate in a given context.
-
E.
heirApparentDuringReign
Indicates that one entity was officially recognized as the designated heir apparent to another entity’s position or title during the latter’s period of reign.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b97acbf4819087b92a8b29baef46 |
completed | March 1, 2026, 10:11 p.m. |
Created at: March 1, 2026, 7:41 p.m.