Triple
T9099987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nogai |
E218126
|
entity |
| Predicate | usesAlphabetBasedOn |
P7160
|
FINISHED |
| Object | Russian Cyrillic alphabet |
—
|
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: Russian Cyrillic alphabet | Statement: [Nogai, usesAlphabetBasedOn, Russian Cyrillic alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAlphabetBasedOn Context triple: [Nogai, usesAlphabetBasedOn, Russian Cyrillic alphabet]
-
A.
usesAlphabet
chosen
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
B.
usesAlphabetResources
Indicates that an entity makes use of alphabet-related resources (such as letters, character sets, or alphabet-based tools) in performing an action or function.
-
C.
usesLatinAlphabetSince
Indicates that an entity has employed the Latin alphabet as its writing system starting from a specific point in time and continuing thereafter.
-
D.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
E.
alphabetType
Indicates the type or classification of an alphabet used by a writing system or language.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9711babc8190a336812dd08d9c73 |
completed | April 1, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:15 p.m.