Triple
T20791222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kårsta |
E511781
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object | Kårsta station |
—
|
NE NERFINISHED |
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: Kårsta station | Statement: [Kårsta, hasRailwayStation, Kårsta station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kårsta station Context triple: [Kårsta, hasRailwayStation, Kårsta station]
-
A.
Kårsta station
chosen
Kårsta station is a railway station in Kårsta, Sweden, serving as the northern terminus of Stockholm's Roslagsbanan narrow-gauge commuter rail network.
-
B.
Gulskogen Station
Gulskogen Station is a railway station in the Drammen area of Viken county, Norway, serving local and regional train traffic.
-
C.
Häggvik station
Häggvik station is a commuter rail station in the Häggvik district of Sollentuna, north of central Stockholm, Sweden.
-
D.
Åkersberga station
Åkersberga station is a local commuter rail stop on the Roslagsbanan narrow-gauge railway serving the suburban town of Åkersberga in Österåker Municipality, Sweden.
-
E.
Skogen station
Skogen station is a small metro stop on Oslo’s Holmenkollen Line (Line 1), serving the hillside residential area of Skogen in the Vestre Aker district.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c29010508190bf2cf577d7f64754 |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:38 p.m.