Triple
T32245840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karen Boyer |
E823743
|
entity |
| Predicate | lifePartnerOfNotablePerson |
P29616
|
FINISHED |
| Object | Gene Wilder |
—
|
NE NERFINISHED |
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: Gene Wilder | Statement: [Karen Boyer, lifePartnerOfNotablePerson, Gene Wilder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lifePartnerOfNotablePerson Context triple: [Karen Boyer, lifePartnerOfNotablePerson, Gene Wilder]
-
A.
lifePartnerOfKeyFigureIn
Indicates that one entity is the life partner (such as spouse or long-term companion) of a key or central figure associated with another entity (such as an organization, event, or work).
-
B.
marriedToNotablePerson
chosen
Indicates that a person is legally married to another individual who is widely recognized or notable.
-
C.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
D.
featuresRealLifeSpouses
Indicates that the work includes a pair of performers who are married to each other in real life.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69f3490cdda88190a9d61e11252a771f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc33ab4c8190ab3bdaa735ceddb6 |
completed | May 3, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:40 a.m.