Triple
T9101589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | «На дне» |
E218169
|
entity |
| Predicate | значимость |
P428
|
FINISHED |
| Object | классика русской драматургии |
—
|
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: классика русской драматургии | Statement: [«На дне», значимость, классика русской драматургии]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: значимость Context triple: [«На дне», значимость, классика русской драматургии]
-
A.
significance
chosen
Indicates that one entity holds particular importance, influence, or meaningful impact in relation to another entity or context.
-
B.
significantAfter
Indicates that one event or state occurs after another in a way that is temporally meaningful or non-trivially later, not just immediately or insignificantly afterward.
-
C.
significantPort
Indicates that a port holds major importance in terms of trade, transportation, or strategic relevance within a given context.
-
D.
hasParticularSignificanceFor
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
E.
peakImportance
Indicates that something reaches or represents the highest level of importance within a given context or timeframe.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc971435d08190b5007ed44ac0a364 |
completed | April 1, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:15 p.m.