Triple
T33509865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richie Aprile |
E858209
|
entity |
| Predicate | victimOfViolence |
P177410
|
FINISHED |
| Object | Beansie Gaeta |
—
|
NE NERFINISHED |
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: Beansie Gaeta | Statement: [Richie Aprile, victimOfViolence, Beansie Gaeta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimOfViolence Context triple: [Richie Aprile, victimOfViolence, Beansie Gaeta]
-
A.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
B.
victimWas
chosen
Indicates that one entity was the victim of an action, event, or harmful behavior carried out by another entity.
-
C.
typeOfVictimization
Indicates the specific kind or category of harmful act, abuse, or exploitation experienced by a victim.
-
D.
abuseSurvivorOf
Indicates that one entity has previously suffered abuse perpetrated by the other entity.
-
E.
victimCategory
Indicates the classification or type of victim associated with an event, action, or harmful outcome.
- 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_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:38 a.m.