Triple
T31135942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margravine consort of Brandenburg-Ansbach |
E793640
|
entity |
| Predicate | typeOfConsort |
P198497
|
FINISHED |
| Object | princely consort |
—
|
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: princely consort | Statement: [Margravine consort of Brandenburg-Ansbach, typeOfConsort, princely consort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfConsort Context triple: [Margravine consort of Brandenburg-Ansbach, typeOfConsort, princely consort]
-
A.
hasTypeOfConsort
chosen
Indicates that an entity has a consort characterized by a specific type or category of consort relationship.
-
B.
linkedToConsort
Indicates a relationship in which one entity is connected or associated to another as its consort (spouse or formal partner).
-
C.
providedConsortTo
Indicates that one entity served as the consort (spouse or partner) to another entity.
-
D.
holderConsort
Indicates a marital or consort relationship in which one entity is the spouse or consort of the title- or office-holding entity.
-
E.
possibleConsortOf
Indicates that one entity is a potential or likely romantic or marital partner of another, without asserting that the relationship is confirmed.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ffb1218cb08190a814c7f0833501a7 |
completed | May 9, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69ffb083d6988190b2757e0cfd629b75 |
completed | May 9, 2026, 10:09 p.m. |
Created at: April 29, 2026, 9:05 p.m.