Triple
T29595403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ippolit |
E754278
|
entity |
| Predicate | relationshipToMainProtagonist |
P201537
|
FINISHED |
| Object | romantic rival of Zhenya Lukashin |
—
|
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: romantic rival of Zhenya Lukashin | Statement: [Ippolit, relationshipToMainProtagonist, romantic rival of Zhenya Lukashin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMainProtagonist Context triple: [Ippolit, relationshipToMainProtagonist, romantic rival of Zhenya Lukashin]
-
A.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
B.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
C.
relativeOfMainCharacter
Indicates that one entity is a family member or relative of the main character entity.
-
D.
isFriendOfProtagonist
Indicates that one entity is a friend or close ally of the story’s main character.
-
E.
relationshipToMain
chosen
Indicates that an entity has a specified type of relationship or association to a primary or main 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a017d27e184819094638c3cf6876de4 |
completed | May 11, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_6a017c785a44819083111384b55769e9 |
completed | May 11, 2026, 6:51 a.m. |
Created at: April 28, 2026, 6:17 p.m.