Triple
T12860836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddy Benson |
E307581
|
entity |
| Predicate | associatedWithScam |
P54348
|
FINISHED |
| Object | confidence tricks |
—
|
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: confidence tricks | Statement: [Freddy Benson, associatedWithScam, confidence tricks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithScam Context triple: [Freddy Benson, associatedWithScam, confidence tricks]
-
A.
isSuspiciousOf
Indicates that one entity believes another entity or situation may be untrustworthy, harmful, or involved in wrongdoing.
-
B.
illegalActivityAssociatedWith
chosen
Indicates that there is a connection between an entity and an unlawful or criminal activity.
-
C.
associatedWithReputation
Indicates a relationship where an entity is linked to, influenced by, or characterized in terms of another entity’s reputation or perceived standing.
-
D.
associatedWithCompromise
Indicates a relationship where an entity is linked to, involved in, or affected by a security compromise or breach.
-
E.
associatedWithUrbanLegend
Indicates a relationship where something is connected to, derived from, or commonly regarded as part of an urban legend.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:37 p.m.