Triple
T13699523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wick |
E328480
|
entity |
| Predicate | otherName |
P39
|
FINISHED |
| Object | Baba Yaga |
E757347
|
NE 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: Baba Yaga | Statement: [John Wick, otherName, Baba Yaga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baba Yaga Context triple: [John Wick, otherName, Baba Yaga]
-
A.
Baba Yaga
chosen
Baba Yaga is a fearsome witch-like figure from Slavic folklore, known for living in a hut on chicken legs and embodying both dangerous and protective supernatural powers.
-
B.
Baba Yaga and Vasilisa the Brave
Baba Yaga and Vasilisa the Brave is a richly illustrated retelling of a classic Russian folktale about a courageous girl who outwits the fearsome witch Baba Yaga.
-
C.
Leshy
Leshy is a forest-dwelling spirit from Slavic mythology, often depicted as a shape-shifting guardian of the woods who can lead travelers astray.
-
D.
Chernomor
Chernomor is a villainous sorcerer with a long magical beard who abducts the heroine in Alexander Pushkin’s narrative poem "Ruslan and Ludmila."
-
E.
Василиса
Василиса — одна из центральных героинь пьесы Максима Горького «На дне», олицетворяющая трагизм и жестокость нищего дна общества.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f794559e9c81909ef8a6d9b9f480b3 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:54 p.m.