Triple
T25059396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Jeanne Baptiste of Savoy-Nemours |
E627613
|
entity |
| Predicate | countryOfRegency |
P162559
|
FINISHED |
| Object | Duchy of Savoy |
—
|
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: Duchy of Savoy | Statement: [Marie Jeanne Baptiste of Savoy-Nemours, countryOfRegency, Duchy of Savoy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfRegency Context triple: [Marie Jeanne Baptiste of Savoy-Nemours, countryOfRegency, Duchy of Savoy]
-
A.
countryOfMonarchy
Indicates that a monarchy is associated with or rules over a particular country.
-
B.
countryOfQueenship
Indicates that a person holds or held the position of queen in the specified country.
-
C.
reinoDeNacimiento
Indicates the kingdom or realm in which an entity was born.
-
D.
countryOfFictionalMonarchy
Indicates the real-world country in which a fictional monarchy is located or to which it belongs.
-
E.
countryOfRegistry
Indicates the country in which an entity (such as a ship, aircraft, or company) is officially registered.
- 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f627ad6d4c81909796d39d78e414f9 |
completed | May 2, 2026, 4:34 p.m. |
Created at: April 18, 2026, 6:09 a.m.