Triple
T20411493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharks as execution method (film) |
E500596
|
entity |
| Predicate | hasTypicalVictimRole |
P140041
|
FINISHED |
| Object | hero |
—
|
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: hero | Statement: [Sharks as execution method (film), hasTypicalVictimRole, hero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalVictimRole Context triple: [Sharks as execution method (film), hasTypicalVictimRole, hero]
-
A.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
B.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
C.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
D.
hasMainVictim
Indicates that an event, action, or harmful situation primarily targets or affects a specific victim as its main subject.
-
E.
allegedVictimOf
Indicates that one entity is claimed or reported to have been harmed, wronged, or victimized by another entity, without asserting that the claim is proven.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3f8fdc8190b05b6c41b38f34b7 |
completed | April 20, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69e5765d7cb48190adec18d6d1e3d263 |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:29 a.m.