Triple
T17894875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vainikkala |
E447406
|
entity |
| Predicate | hasBorderStationStatus |
P13728
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Vainikkala, hasBorderStationStatus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderStationStatus Context triple: [Vainikkala, hasBorderStationStatus, yes]
-
A.
hasBoundaryStations
Indicates that an entity is associated with specific stations that mark its boundary or endpoints.
-
B.
hasAdjacentStationOnBorderlandsLine
Indicates that one station is directly next to another station along the Borderlands Line.
-
C.
hasBorderFacilityType
Indicates that a border facility possesses or is classified by a specific type or category of border-related infrastructure or service.
-
D.
hasBorderRailwayStationWith
Indicates that two regions share a common border at which there is a railway station connecting or serving both sides.
-
E.
hasBorderControlStatus
chosen
Indicates the type or condition of border control that applies to a given entity or location.
- F. None of above.
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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49d7ccf808190b4c1fd477043bcc8 |
completed | April 19, 2026, 9:16 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e9b77c8190bbfb508f28dfacfa |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:19 a.m.