Triple
T5041190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grodno Governorate |
E113547
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Slonim |
E391527
|
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: Slonim | Statement: [Grodno Governorate, contains, Slonim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slonim Context triple: [Grodno Governorate, contains, Slonim]
-
A.
Koserow
Koserow is a seaside resort village on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its beaches and coastal landscapes.
-
B.
Kraśnik
Kraśnik is a town in eastern Poland known for its historical architecture and location within the Lublin region.
-
C.
Mikolow
Mikolow is a town in southern Poland’s Silesian Voivodeship, known for its historic center and proximity to the regional capital Katowice.
-
D.
Dzyarzhynsk
chosen
Dzyarzhynsk is a town in Belarus known for its proximity to Dzyarzhynskaya Hara, the country’s highest point.
-
E.
Lublinitz
Lublinitz is the former German name for the town of Lubliniec, located in southern Poland’s Silesian region.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73de73008190b89aec9a76b43e4f |
completed | March 20, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c8414288190bf53a40033aa70ea |
completed | March 21, 2026, 1:26 p.m. |
Created at: March 20, 2026, 1:37 p.m.