Triple
T114152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zyklon B |
E2306
|
entity |
| Predicate | effectOnVictims |
P1634
|
FINISHED |
| Object | rapid suffocation and death |
—
|
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: rapid suffocation and death | Statement: [Zyklon B, effectOnVictims, rapid suffocation and death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnVictims Context triple: [Zyklon B, effectOnVictims, rapid suffocation and death]
-
A.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
B.
victimGroup
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
C.
primaryEffect
chosen
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
D.
affectedAgency
Indicates that one entity has an effect on, or causes a change in, the agency or capacity for action of another entity.
-
E.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.