Triple
T22310486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belorusskaya metro station |
E551497
|
entity |
| Predicate | hasNativeName |
P1435
|
FINISHED |
| Object | Белорусская |
—
|
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: Белорусская | Statement: [Belorusskaya metro station, hasNativeName, Белорусская]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Белорусская Context triple: [Belorusskaya metro station, hasNativeName, Белорусская]
-
A.
Belarusian language
The Belarusian language is an East Slavic language primarily spoken in Belarus and recognized as one of its official state languages.
-
B.
Standard Belarusian
Standard Belarusian is the codified modern form of the Belarusian language used in official communication, education, and literature in Belarus.
-
C.
Belarusians
Belarusians are an East Slavic ethnic group primarily associated with the modern nation of Belarus, sharing linguistic, cultural, and historical ties with Russians and Ukrainians.
-
D.
Belorusskaya
chosen
Belorusskaya is a Moscow Metro station that serves as a key transport hub and interchange point near Belorussky railway terminal.
-
E.
Russin
Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1574e7fc0819080e3e85001ab2c90 |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.