Triple
T34664096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bashkirs |
E890201
|
entity |
| Predicate | censusCountry |
P45218
|
FINISHED |
| Object | Russian Federation |
—
|
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: Russian Federation | Statement: [Bashkirs, censusCountry, Russian Federation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: censusCountry Context triple: [Bashkirs, censusCountry, Russian Federation]
-
A.
collectionCountry
Indicates the country in which an item, specimen, or data was collected.
-
B.
census
chosen
Indicates that an official count or survey is conducted to determine the number and characteristics of a population within a defined area or group.
-
C.
coveredCountry
Indicates that one entity includes or provides coverage for the territory or jurisdiction of a specified country.
-
D.
hasPopulationCountry
Indicates that a specified population size is associated with, or belongs to, a particular country.
-
E.
countryAssessed
Indicates that a particular country has been evaluated or examined according to a specified assessment, criteria, or process.
- 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f722f429e8819087d585e9976f0024 |
completed | May 3, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:04 a.m.