Triple
T14098049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sedova |
E339305
|
entity |
| Predicate | usedInCountry |
P715
|
FINISHED |
| Object | Belarus |
E13665
|
NE 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: Belarus | Statement: [Sedova, usedInCountry, Belarus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belarus Context triple: [Sedova, usedInCountry, Belarus]
-
A.
Belarus
chosen
Belarus is an Eastern European country known for its flat landscapes, dense forests, and historical ties to both the Soviet Union and the broader Slavic cultural sphere.
-
B.
Belarus–Russia
Belarus–Russia refers to the shared border area and bilateral relationship between the Republic of Belarus and the Russian Federation, encompassing close political, economic, and cultural ties.
-
C.
Belarus and Latvia
Belarus and Latvia are neighboring Eastern European countries that were selected to jointly host the 2021 IIHF Ice Hockey World Championship.
-
D.
Belarus–Poland
Belarus–Poland refers to the international border region where Belarus and Poland meet, encompassing shared historical, cultural, and ecological landscapes.
-
E.
Belorusskaya
Belorusskaya is a Moscow Metro station that serves as a key transport hub and interchange point near Belorussky railway terminal.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb926288190a7f0f50d1d585d76 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0adfc28819097a1bfd56739c286 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:22 p.m.