Triple
T21357513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuri Bogolyubsky |
E526672
|
entity |
| Predicate | maritalOrderWithQueenTamar |
P143974
|
FINISHED |
| Object | second husband |
—
|
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: second husband | Statement: [Yuri Bogolyubsky, maritalOrderWithQueenTamar, second husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalOrderWithQueenTamar Context triple: [Yuri Bogolyubsky, maritalOrderWithQueenTamar, second husband]
-
A.
maritalConferment
Indicates the act of formally granting, bestowing, or recognizing a marital status or marriage-related rights between entities.
-
B.
marriageOrderWithCatherineParr
Indicates the sequence or relative ordering of marriages involving Catherine Parr in relation to another spouse or marriage event.
-
C.
maritalOrderWithDeanMartin
Indicates that there exists a marital relationship involving Dean Martin, specifying the order or sequence of that marriage among multiple marriages.
-
D.
marriedToHeiress
Indicates that a person is married to someone who is an heiress.
-
E.
marriageFormedBy
Indicates that a marriage relationship was created or brought into existence by a specific event, action, or process.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8afa2d11c81908608851940e4e6d3 |
completed | April 22, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e61b3e47f881908fb2aac9bd2bfb58 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 16, 2026, 5:07 p.m.