Triple
T910877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne, Princess Royal |
E19653
|
entity |
| Predicate | startTime (marriage to Mark Phillips) |
P14428
|
FINISHED |
| Object | 1973 |
—
|
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: 1973 | Statement: [Anne, Princess Royal, startTime (marriage to Mark Phillips), 1973]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime (marriage to Mark Phillips) Context triple: [Anne, Princess Royal, startTime (marriage to Mark Phillips), 1973]
-
A.
spouseStartTime
chosen
Indicates the point in time when two individuals began their spousal (marriage) relationship.
-
B.
marriageDate
Indicates the specific date on which two entities entered into a marital relationship.
-
C.
ageAtMarriage
Indicates the age a person was when they got married.
-
D.
spouseRelationshipEnd
Indicates that a marital relationship between two individuals has ended, such as through divorce, annulment, or separation.
-
E.
numberOfMarriagesOfSpouse
Indicates the total count of times the referenced spouse has been married.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.