Triple
T36497172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank DeTorri |
E899221
|
entity |
| Predicate | hasUnhealthyLifestyle |
P157391
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Frank DeTorri, hasUnhealthyLifestyle, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnhealthyLifestyle Context triple: [Frank DeTorri, hasUnhealthyLifestyle, true]
-
A.
hasRiskFactorFor
Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
-
B.
healthHabit
chosen
Indicates a relationship where an entity regularly engages in a behavior or practice that affects its health or well-being.
-
C.
hasHealthGoal
Indicates that an entity has a specific health-related objective or target it is aiming to achieve.
-
D.
requiresLifestyleModification
Indicates that one entity necessitates a change or adjustment in another entity’s lifestyle, habits, or daily behaviors.
-
E.
hasHabit
Indicates that an entity regularly performs, practices, or exhibits a particular behavior or routine.
- 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
Created at: May 3, 2026, 4:10 p.m.