Triple
T29133693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Sun |
E738448
|
entity |
| Predicate | hasTortureScene |
P180428
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Colonel Sun, hasTortureScene, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTortureScene Context triple: [Colonel Sun, hasTortureScene, yes]
-
A.
useOfTorture
Indicates the intentional infliction or use of torture by one entity upon another, typically to punish, coerce, intimidate, or extract information.
-
B.
torturedAt
Indicates that an entity was subjected to torture at a specific location or facility.
-
C.
resultOfTorture
Indicates that something occurs as a direct consequence or outcome of an act of torture.
-
D.
allegedTorture
Indicates that an entity is claimed or reported to have committed, experienced, or been involved in an act of torture, without asserting that the torture is proven.
-
E.
hasCourtroomScenes
Indicates that the work contains one or more scenes set in a courtroom or depicting courtroom proceedings.
- F. None of above. chosen
Provenance (4 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
| PDg | Predicate description generation | batch_69f74061c440819080434155c2d60341 |
completed | May 3, 2026, 12:32 p.m. |
Created at: April 28, 2026, 11:33 a.m.