Triple
T21476184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gnesta |
E529866
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object | Gnesta railway 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: Gnesta railway station | Statement: [Gnesta, hasRailwayStation, Gnesta railway station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gnesta railway station Context triple: [Gnesta, hasRailwayStation, Gnesta railway station]
-
A.
Gnesta Station
chosen
Gnesta Station is a key railway station in the town of Gnesta, Sweden, serving as an important terminus and hub on the Stockholm commuter rail network.
-
B.
Östberga station
Östberga station is a local railway stop serving the suburban area of Djursholm in the Stockholm metropolitan region of Sweden.
-
C.
Gulskogen Station
Gulskogen Station is a railway station in the Drammen area of Viken county, Norway, serving local and regional train traffic.
-
D.
Rönninge station
Rönninge station is a commuter rail station in Rönninge, Sweden, serving as part of the Stockholm commuter rail network.
-
E.
Häggvik station
Häggvik station is a commuter rail station in the Häggvik district of Sollentuna, north of central Stockholm, Sweden.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1737f881908ef7889e9568a4d3 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:20 p.m.