Triple
T6625733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Białystok railway station |
E149794
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Sokółka |
E287212
|
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: Sokółka | Statement: [Białystok railway station, connectsTo, Sokółka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sokółka Context triple: [Białystok railway station, connectsTo, Sokółka]
-
A.
Sokółka
chosen
Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
-
B.
Sokołówka
Sokołówka is a small river in Poland known for flowing through the city of Łódź and its surrounding areas.
-
C.
Kurzętnik
Kurzętnik is a village in northern Poland known for its historical character and location within the picturesque Warmian-Masurian region.
-
D.
Sukiennice
Sukiennice is a historic Renaissance cloth hall and landmark market building located in the main square of Kraków, Poland.
-
E.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af8187d881908b7a86f2cae5de23 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eee8740881908b4fafb12db6b7f3 |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 1:58 p.m.