Triple
T34920627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Martin as George Banks |
E1007123
|
entity |
| Predicate | weddingRelation |
P110874
|
FINISHED |
| Object | father of the bride |
—
|
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: father of the bride | Statement: [Steve Martin as George Banks, weddingRelation, father of the bride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingRelation Context triple: [Steve Martin as George Banks, weddingRelation, father of the bride]
-
A.
maritalRelations
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
-
B.
associatedWithWeddingOf
chosen
Indicates a relationship where something is connected or related to the wedding event of specific individuals.
-
C.
relationshipToSpouse
Indicates the specific familial or social role one person holds in relation to their spouse (e.g., husband, wife, partner).
-
D.
characterRelativeByMarriage
Indicates that one character is related to another through marriage rather than by blood.
-
E.
spouseRelative
Indicates that one person is related to another through the marriage of at least one of them (e.g., in-laws or relatives by marriage).
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.