Triple
T17709870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sviatoshynsko–Brovarska line |
E441533
|
entity |
| Predicate | servesBank |
P128674
|
FINISHED |
| Object | right bank of Dnipro River |
—
|
LITERAL 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: right bank of Dnipro River | Statement: [Sviatoshynsko–Brovarska line, servesBank, right bank of Dnipro River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesBank Context triple: [Sviatoshynsko–Brovarska line, servesBank, right bank of Dnipro River]
-
A.
connectsBank
Indicates a relationship where one entity serves to link or provide access between another entity and a bank or banking service.
-
B.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
C.
hasBanking
Indicates that one entity provides or is associated with banking services or facilities for another entity.
-
D.
hasFinancialInstitution
Indicates that one entity is associated with or linked to a financial institution, such as a bank or similar financial service provider.
-
E.
banksOften
Indicates that the subject frequently or habitually engages in banking activities with the object (such as depositing, withdrawing, or otherwise using banking services).
- F. None of above. chosen
Provenance (4 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729a9a9c81908d65ff0bda12c961 |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d018227c8190b6624a2199e765e8 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 10, 2026, 10:05 a.m.