Triple
T15543112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petrovskiy |
E370530
|
entity |
| Predicate | typicalCyrillicSpelling |
P118020
|
FINISHED |
| Object | Петровский |
—
|
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: Петровский | Statement: [Petrovskiy, typicalCyrillicSpelling, Петровский]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCyrillicSpelling Context triple: [Petrovskiy, typicalCyrillicSpelling, Петровский]
-
A.
hasTypicalSpelling
Indicates that one form is the standard or commonly accepted spelling of another form.
-
B.
typicalTransliterationFrom
Indicates that one string is the standard or most commonly used transliteration of another string from one writing system to another.
-
C.
CyrillicName
chosen
Indicates that an entity has a name written in the Cyrillic script.
-
D.
usesFixedSpellingsForCommonSyllables
Indicates that an entity consistently applies predetermined, standard spellings for frequently occurring syllables.
-
E.
usesStandardOrthographyOf
Indicates that one entity writes or represents language according to the standard orthographic system defined for another 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04432c3808190bb5b653bf8de30c6 |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:07 a.m.