Triple
T23014956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S3 line |
E573005
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Erkner 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: Erkner station | Statement: [S3 line, serves, Erkner station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erkner station Context triple: [S3 line, serves, Erkner station]
-
A.
Erkner station
chosen
Erkner station is a railway station in the town of Erkner, Germany, serving as a regional and S-Bahn commuter hub near Berlin.
-
B.
Hanaborg Station
Hanaborg Station is a local railway stop serving the residential area of Hanaborg in Lørenskog, just east of Oslo, Norway.
-
C.
Bachman station
Bachman station is a public transit stop in Dallas, Texas, served by DART’s Green Line light rail system.
-
D.
Vestby Station
Vestby Station is a railway station in Vestby, Norway, serving as a stop on the Østfold Line for regional and commuter trains.
-
E.
Stange Station
Stange Station is a railway station serving the village of Stange in Innlandet county, Norway, providing regional and intercity train connections.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e3c0e08190a7ac747b056ec3ca |
completed | April 29, 2026, 4:06 a.m. |
Created at: April 17, 2026, 3:51 p.m.