Triple
T9421459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysaker Station |
E227160
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | SJ Norge |
E119734
|
NE 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: SJ Norge | Statement: [Lysaker Station, servedBy, SJ Norge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SJ Norge Context triple: [Lysaker Station, servedBy, SJ Norge]
-
A.
SJ Norge
chosen
SJ Norge is a Norwegian railway company operating passenger train services on key routes across Norway.
-
B.
Osedalen
Osedalen is a village in Froland municipality in Agder county in southern Norway.
-
C.
Storlien
Storlien is a village and ski resort in central Sweden near the Norwegian border, known for its winter sports and cross-border rail connections.
-
D.
Skeid
Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
-
E.
MET Norway
MET Norway is Norway's national meteorological service, responsible for weather forecasting, climate research, and related public services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c2651c48190808281779fab49df |
completed | April 1, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107c95c9481909957b99cacf5e045 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:48 p.m.