Triple
T1766932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth Christine of Brunswick-Wolfenbüttel |
E38783
|
entity |
| Predicate | spouseType |
P31663
|
FINISHED |
| Object | marriage by proxy to Charles VI |
—
|
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: marriage by proxy to Charles VI | Statement: [Elisabeth Christine of Brunswick-Wolfenbüttel, spouseType, marriage by proxy to Charles VI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseType Context triple: [Elisabeth Christine of Brunswick-Wolfenbüttel, spouseType, marriage by proxy to Charles VI]
-
A.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
B.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
C.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
D.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
E.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab39fc2c448190bfaf1ee8d474632a |
completed | March 6, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69aa61cbb1288190a7ba38b61905f578 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab39faf69c8190bae98d3e3911078f |
completed | March 6, 2026, 8:32 p.m. |
Created at: March 4, 2026, 7:31 p.m.