Triple
T20618988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nitram |
E506646
|
entity |
| Predicate | avoidsDepicting |
P33022
|
FINISHED |
| Object | actual massacre on screen |
—
|
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: actual massacre on screen | Statement: [Nitram, avoidsDepicting, actual massacre on screen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avoidsDepicting Context triple: [Nitram, avoidsDepicting, actual massacre on screen]
-
A.
hasNoDepictionOf
chosen
Indicates that the subject lacks any visual or graphical representation of the specified object or concept.
-
B.
supportsDepictionOf
Indicates that one entity provides the medium, context, or framework that enables the depiction or representation of another entity.
-
C.
rarelyDepicts
Indicates that one entity infrequently or only in exceptional cases portrays, represents, or shows another entity.
-
D.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
-
E.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.