Triple
T4284884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Adélaïde, Grand Duchess of Luxembourg |
E97242
|
entity |
| Predicate | wasUnmarried |
P6807
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Marie-Adélaïde, Grand Duchess of Luxembourg, wasUnmarried, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasUnmarried Context triple: [Marie-Adélaïde, Grand Duchess of Luxembourg, wasUnmarried, true]
-
A.
neverMarried
chosen
Indicates that the subject has not been legally married to any partner at any time up to the present.
-
B.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
C.
marriedBefore
Indicates that one entity entered into a marriage at an earlier time than the other entity.
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3505bff588190919a4ef547f607c2 |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.