Triple
T3483340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annette Kaye |
E73546
|
entity |
| Predicate | marriageDurationDescription |
P47544
|
FINISHED |
| Object | brief marriage to Larry King |
—
|
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: brief marriage to Larry King | Statement: [Annette Kaye, marriageDurationDescription, brief marriage to Larry King]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageDurationDescription Context triple: [Annette Kaye, marriageDurationDescription, brief marriage to Larry King]
-
A.
marriageDate
Indicates the specific date on which two entities entered into a marital relationship.
-
B.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
C.
relationshipDurationWith
chosen
Indicates the length of time that a specified relationship between two entities has existed or is expected to last.
-
D.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
E.
ageAtMarriage
Indicates the age a person was when they got 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb781e9c8190810fdd814f506127 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.