Triple
T6618826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Saxony |
E149622
|
entity |
| Predicate | hasMaritalBasis |
P16214
|
FINISHED |
| Object | legally recognized marriage to the duke |
—
|
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: legally recognized marriage to the duke | Statement: [Duchess of Saxony, hasMaritalBasis, legally recognized marriage to the duke]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalBasis Context triple: [Duchess of Saxony, hasMaritalBasis, legally recognized marriage to the duke]
-
A.
maritalBasis
chosen
Indicates that the relationship or status in question is founded on, justified by, or determined due to a marital relationship between the involved entities.
-
B.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
C.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
D.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
E.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:58 p.m.