Triple
T16003596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Roulette |
E388153
|
entity |
| Predicate | legalStatusInMostCountries |
P120728
|
FINISHED |
| Object | illegal if resulting in harm or 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: illegal if resulting in harm or death | Statement: [Russian Roulette, legalStatusInMostCountries, illegal if resulting in harm or death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusInMostCountries Context triple: [Russian Roulette, legalStatusInMostCountries, illegal if resulting in harm or death]
-
A.
legalStatusInManyCountries
Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
-
B.
hasHighestLegalStatusWithinCountry
Indicates that an entity holds the topmost legally recognized status or rank within a specific country, above all other comparable statuses.
-
C.
legalStatusVariesBy
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
D.
legalStatusOfItems
Indicates the legal classification or regulatory standing that applies to specified items.
-
E.
legalStatusAccordingToIndia
Indicates the legal status or classification of an entity as defined specifically by the laws and regulations of India.
- 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_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. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:55 a.m.