Triple
T1324739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Canino and Musignano |
E28299
|
entity |
| Predicate | relatedHouse |
P26313
|
FINISHED |
| Object | Bonaparte-Murat connections |
—
|
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: Bonaparte-Murat connections | Statement: [Prince of Canino and Musignano, relatedHouse, Bonaparte-Murat connections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedHouse Context triple: [Prince of Canino and Musignano, relatedHouse, Bonaparte-Murat connections]
-
A.
associatedHouse
chosen
Indicates a relationship where one entity is linked or connected to a particular house, typically as its related or corresponding house.
-
B.
houses
Indicates that one entity serves as a dwelling or shelter for another entity.
-
C.
associatedHeir
Indicates that one entity is designated or recognized as the heir connected to, or inheriting from, another entity.
-
D.
relatedPlace
Indicates a relationship where one place is connected or associated with another place in a relevant or meaningful way.
-
E.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19e81c0819092f85201ae34422a |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.