Triple
T30445619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Вальс цветов |
E774568
|
entity |
| Predicate | связан с персонажами |
P169771
|
FINISHED |
| Object | цветы |
—
|
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: цветы | Statement: [Вальс цветов, связан с персонажами, цветы]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: связан с персонажами Context triple: [Вальс цветов, связан с персонажами, цветы]
-
A.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
B.
fictionalCharacterAssociatedWith
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
C.
relatedCharacterType
Indicates that one character has a specified type of relationship or role in connection to another character.
-
D.
relatedCharacterContext
Indicates a contextual relationship between characters, such as roles, interactions, or situational connections that link them within a specific narrative or setting.
-
E.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
- 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f686be108c8190a8ec98dc286ab03b |
completed | May 2, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 29, 2026, 8:08 p.m.