Triple
T18548706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany Stewart |
E453307
|
entity |
| Predicate | spouseNetWorthCategory |
P79314
|
FINISHED |
| Object | billionaire |
—
|
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: billionaire | Statement: [Tiffany Stewart, spouseNetWorthCategory, billionaire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNetWorthCategory Context triple: [Tiffany Stewart, spouseNetWorthCategory, billionaire]
-
A.
spouseWealthStatus
chosen
Indicates the financial status or wealth level of a person’s spouse in relation to that person.
-
B.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
C.
spouseCollective
Indicates that a group of individuals collectively stand in a spousal or marriage-like relationship to another group or entity.
-
D.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e534be2298819095f637065fc2724e |
completed | April 19, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:38 a.m.