Triple
T6924673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Françoise Athénaïs de Rochechouart de Mortemart |
E160274
|
entity |
| Predicate | numberOfChildrenWith |
P29785
|
FINISHED |
| Object | 7 children with Louis XIV of France |
—
|
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 children with Louis XIV of France | Statement: [Françoise Athénaïs de Rochechouart de Mortemart, numberOfChildrenWith, 7 children with Louis XIV of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChildrenWith Context triple: [Françoise Athénaïs de Rochechouart de Mortemart, numberOfChildrenWith, 7 children with Louis XIV of France]
-
A.
numberOfChildren
Indicates the total count of children that an entity has.
-
B.
childrenWith
chosen
Indicates that two or more entities share one or more children together as parents or guardians.
-
C.
childStatus
Indicates the current condition, role, or state of a child entity in relation to its parent or context.
-
D.
adoptedChildren
Indicates that one entity has legally taken another entity as their child through adoption.
-
E.
numberOfSons
Indicates the count of male offspring that an entity has.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da18b6388190947dfc1eb9e5d382 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.