Triple
T137566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrei |
E2779
|
entity |
| Predicate | scriptVariantLanguage |
P5922
|
FINISHED |
| Object | Russian |
—
|
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 | Statement: [Andrei, scriptVariantLanguage, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptVariantLanguage Context triple: [Andrei, scriptVariantLanguage, Russian]
-
A.
scriptType
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
-
B.
script
Indicates that an entity is associated with a written text or code (such as a screenplay, program, or written instructions) that defines its content or behavior.
-
C.
scriptDirection
Indicates the direction in which a writing system or script is read or written (e.g., left-to-right, right-to-left, top-to-bottom).
-
D.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
E.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
- F. None of above. chosen
Provenance (4 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a6cab88190944c8f74d8d1605c |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.