Triple
T24339462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Надежда |
E613472
|
entity |
| Predicate | транслитерацияНаАнглийский |
P62529
|
FINISHED |
| Object | Nadezhda |
—
|
NE NERFINISHED |
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: Nadezhda | Statement: [Надежда, транслитерацияНаАнглийский, Nadezhda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: транслитерацияНаАнглийский Context triple: [Надежда, транслитерацияНаАнглийский, Nadezhda]
-
A.
transliterationTarget
chosen
Indicates that one entity is the target script or form into which another entity is transliterated.
-
B.
transliterationLanguage
Indicates the language whose writing system is used as the target when converting text from one script to another.
-
C.
standardTransliteration
Indicates that one representation of text is a transliteration of another according to a recognized standard or convention.
-
D.
typicalTransliterationFrom
Indicates that one string is the standard or most commonly used transliteration of another string from one writing system to another.
-
E.
textTranslation
Indicates a relationship where one text is rendered into another language or form while preserving its original meaning.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932324e8819082344cf42eddc274 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:57 a.m.