Triple
T10935439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Шивелуч |
E258320
|
entity |
| Predicate | известенС |
P96713
|
FINISHED |
| Object | исторические извержения с XVIII века |
—
|
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: исторические извержения с XVIII века | Statement: [Шивелуч, известенС, исторические извержения с XVIII века]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: известенС Context triple: [Шивелуч, известенС, исторические извержения с XVIII века]
-
A.
известенКак
Indicates that one entity is known or recognized by a particular name, title, or role.
-
B.
известноКак
Indicates that one entity is known or referred to by another name, designation, or alias.
-
C.
knownIn
Indicates that an entity is recognized, acknowledged, or familiar within a particular context, domain, or group.
-
D.
isWidelyKnown
Indicates that something is generally recognized or familiar to a large number of people.
-
E.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
- 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.