Triple
T13605935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergiy |
E325060
|
entity |
| Predicate | isSpellingVariantIn |
P457
|
FINISHED |
| Object | Ukrainian-to-English transliteration |
—
|
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: Ukrainian-to-English transliteration | Statement: [Sergiy, isSpellingVariantIn, Ukrainian-to-English transliteration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSpellingVariantIn Context triple: [Sergiy, isSpellingVariantIn, Ukrainian-to-English transliteration]
-
A.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
B.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
D.
spellingIncludes
Indicates that the spelling of one entity contains, as a substring or component, the spelling of another entity.
-
E.
orthographicVariant
Indicates that two written forms are different spellings or orthographic representations of the same linguistic item.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.