Triple
T176393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian language |
E3584
|
entity |
| Predicate | typicalWordOrder |
P1249
|
FINISHED |
| Object | SVO |
—
|
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: SVO | Statement: [Russian language, typicalWordOrder, SVO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWordOrder Context triple: [Russian language, typicalWordOrder, SVO]
-
A.
hasBasicWordOrder
chosen
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
-
B.
grammaticalStructure
Indicates the way linguistic elements are organized and related within a sentence or phrase according to grammatical rules.
-
C.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
D.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
E.
subsequentOrder
Indicates that one order occurs after or follows another order in sequence.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258e497788190aeb61d981efb4d1d |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25669d99481908c5e82ba8641205a |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.