Triple
T3033711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillehammer railway station |
E82956
|
entity |
| Predicate | servedByOperator |
P5884
|
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: [Lillehammer railway station, servedByOperator, SJ Norge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SJ Norge Context triple: [Lillehammer railway station, servedByOperator, 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.
Skedsmo
Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
-
D.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
-
E.
Rødenes
Rødenes is a small village and former municipality in southeastern Norway, known for its rural landscape and historic church.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9af13ce48190bda4f5ca0ffe6285 |
completed | March 8, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dec30d8081909d6ee691e5e51434 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.