Triple
T3331665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Wilson |
E70045
|
entity |
| Predicate | spouseRelationship |
P31663
|
FINISHED |
| Object | cuckolded husband of Myrtle Wilson |
—
|
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: cuckolded husband of Myrtle Wilson | Statement: [George Wilson, spouseRelationship, cuckolded husband of Myrtle Wilson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseRelationship Context triple: [George Wilson, spouseRelationship, cuckolded husband of Myrtle Wilson]
-
A.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
B.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
C.
spouseType
chosen
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
D.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
E.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
- 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_69ad85a24f208190bcf83131bfed3521 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb19358e48190a503af01b92273a4 |
completed | March 8, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.