Triple
T24679081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Kramden |
E611072
|
entity |
| Predicate | hasSpouseDynamic |
P33561
|
FINISHED |
| Object | bickering but loving marriage with Ralph Kramden |
—
|
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: bickering but loving marriage with Ralph Kramden | Statement: [Alice Kramden, hasSpouseDynamic, bickering but loving marriage with Ralph Kramden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpouseDynamic Context triple: [Alice Kramden, hasSpouseDynamic, bickering but loving marriage with Ralph Kramden]
-
A.
hasSpousePositionInFamily
Indicates that a person’s spouse holds a specific role or position within the family structure.
-
B.
spouseAssociatedWith
chosen
Indicates a marital or spousal relationship or close association between two entities.
-
C.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
D.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
E.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
- 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_69e2c4d5c2dc8190ac857dea25ec6ce9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:08 a.m.