Triple
T28405159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Impératrice des Français |
E719506
|
entity |
| Predicate | secondHolderSpouse |
P191001
|
FINISHED |
| Object | Napoleon I of France |
—
|
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: Napoleon I of France | Statement: [Impératrice des Français, secondHolderSpouse, Napoleon I of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondHolderSpouse Context triple: [Impératrice des Français, secondHolderSpouse, Napoleon I of France]
-
A.
thirdHolderSpouse
Indicates that the spouse of the third holder in a sequence or group is related to another specified entity.
-
B.
firstHolderSpouseOf
Indicates that the first holder in the relation is the spouse (married partner) of the other holder.
-
C.
secondWifeOf
Indicates that one person is the second spouse (by order of marriage) of another person.
-
D.
secondHusbandInstanceOf
Indicates that one person is the second husband of another person in a sequence of marital relationships.
-
E.
exSpouse
Indicates that two people were formerly married to each other but are no longer spouses.
- 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_69eff6efd1b08190ae3cefd4f11388a2 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: April 28, 2026, 1:22 a.m.