Triple
T8243836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boogeyman |
E192799
|
entity |
| Predicate | hasViolenceLevel |
P80416
|
FINISHED |
| Object | moderate to graphic |
—
|
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: moderate to graphic | Statement: [The Boogeyman, hasViolenceLevel, moderate to graphic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViolenceLevel Context triple: [The Boogeyman, hasViolenceLevel, moderate to graphic]
-
A.
violenceLevel
chosen
Indicates the degree or intensity of violent behavior, actions, or content present in or associated with an entity.
-
B.
hasTypeOfViolence
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
C.
peakViolencePeriod
Indicates the time period during which violence reaches its highest intensity or frequency within a given context.
-
D.
justifiesViolenceThrough
Indicates that one party legitimizes or defends the use of violence by appealing to, or reasoning through, another factor, belief, or circumstance.
-
E.
usedViolenceAgainst
Indicates that one entity intentionally inflicted physical force or harm upon 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78711f5081909c2f357334491a07 |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.