Triple
T10935455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Шивелуч |
E258320
|
entity |
| Predicate | имеетКодОпасностиДляАвиации |
P96716
|
FINISHED |
| Object | часто оранжевый или красный |
—
|
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: часто оранжевый или красный | Statement: [Шивелуч, имеетКодОпасностиДляАвиации, часто оранжевый или красный]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: имеетКодОпасностиДляАвиации Context triple: [Шивелуч, имеетКодОпасностиДляАвиации, часто оранжевый или красный]
-
A.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
B.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
C.
hasObjectiveHazards
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
-
D.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
E.
hasEmergencyAirstrip
Indicates that an entity possesses or includes an airstrip specifically designated and equipped for emergency use.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770aee178819082c1671a37ff7d82 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.