Triple
T7436736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Valet |
E171633
|
entity |
| Predicate | involvesAffair |
P23617
|
FINISHED |
| Object | billionaire and famous model |
—
|
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 and famous model | Statement: [The Valet, involvesAffair, billionaire and famous model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesAffair Context triple: [The Valet, involvesAffair, billionaire and famous model]
-
A.
hasAffairWith
chosen
Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
-
B.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
-
C.
spouseInvolvedIn
Indicates that a person's spouse participates in, is associated with, or plays a role in a specified activity, event, or situation.
-
D.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
E.
reactionToAffair
Indicates how an entity responds emotionally or behaviorally to an affair or infidelity involving 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f349399c8190b46d5882ece2e73a |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.