Triple
T16003361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Man Down |
E388148
|
entity |
| Predicate | featuresGunViolence |
P7135
|
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: [Man Down, featuresGunViolence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresGunViolence Context triple: [Man Down, featuresGunViolence, true]
-
A.
violenceLedTo
Indicates that an act or state of violence caused or directly resulted in a subsequent event, condition, or outcome.
-
B.
viewOnViolence
Indicates an entity’s stance, opinion, or attitude toward the use of violence.
-
C.
notableViolentCase
Indicates that an entity is associated with a specific case or incident that is recognized as involving significant or noteworthy violence.
-
D.
gun
chosen
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or context.
-
E.
containsViolence
Indicates that the subject includes, depicts, or involves acts of physical harm, aggression, or violent behavior.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.