Triple
T3033715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillehammer railway station |
E82956
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Dombås |
E302488
|
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: Dombås | Statement: [Lillehammer railway station, connectsTo, Dombås]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dombås Context triple: [Lillehammer railway station, connectsTo, Dombås]
-
A.
Dombås
chosen
Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
-
B.
Porsgrunn
Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
-
C.
Skien
Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
-
D.
Østerås
Østerås is a suburban area in Bærum, Norway, best known as the western endpoint of one of the Oslo Metro lines.
-
E.
Larvik
Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
- 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_69b23599a09081909581ac90fcc55ac2 |
completed | March 12, 2026, 3:40 a.m. |
Created at: March 8, 2026, 3:01 p.m.