Triple
T21264129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany Rivers |
E524080
|
entity |
| Predicate | spouseRetirementContext |
P143427
|
FINISHED |
| Object | post-NFL family life |
—
|
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: post-NFL family life | Statement: [Tiffany Rivers, spouseRetirementContext, post-NFL family life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseRetirementContext Context triple: [Tiffany Rivers, spouseRetirementContext, post-NFL family life]
-
A.
spouseRelationshipContext
Indicates a marital relationship context between two entities, specifying that they are spouses or partners in a recognized marriage-like union.
-
B.
spouseInWork
Indicates that two entities are spouses within the context of a particular work (such as a book, film, or series), rather than in real life.
-
C.
spouseMember
Indicates that one entity is the spouse (married partner) of another entity.
-
D.
spouseCollective
Indicates that a group of individuals collectively stand in a spousal or marriage-like relationship to another group or entity.
-
E.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
- F. None of above. chosen
Provenance (4 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735ea74e0819099d724de95996c90 |
completed | April 21, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f9943ed881909ef49045c5bcf6df |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 4 p.m.