Triple
T23928806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Лазарь Маркович Лисицкий |
E602432
|
entity |
| Predicate | влиял на |
P9
|
FINISHED |
| Object | международный модернистский дизайн |
—
|
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: международный модернистский дизайн | Statement: [Лазарь Маркович Лисицкий, влиял на, международный модернистский дизайн]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: влиял на Context triple: [Лазарь Маркович Лисицкий, влиял на, международный модернистский дизайн]
-
A.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
B.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
C.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
D.
incorporatesInfluence
Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
-
E.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
- 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf9a18248190b20991969921ecfd |
completed | April 29, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:54 p.m.