Triple
T18113642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen Line |
E433542
|
entity |
| Predicate | junctionStation |
P14465
|
FINISHED |
| Object | Myrdal |
—
|
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: Myrdal | Statement: [Bergen Line, junctionStation, Myrdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myrdal Context triple: [Bergen Line, junctionStation, Myrdal]
-
A.
Myrdal
chosen
Myrdal is a remote mountain railway station in Norway that serves as a key junction between the Bergen Line and the scenic Flåm Line.
-
B.
Malaueg
Malaueg is an Austronesian language spoken by the Malaueg people in the northern Philippines, particularly in the province of Cagayan.
-
C.
Alva Myrdal
Alva Myrdal was a Swedish sociologist, diplomat, and politician who received the Nobel Peace Prize in 1982 for her work on nuclear disarmament.
-
D.
Hägerstrand
Hägerstrand is a Swedish surname most notably associated with Torsten Hägerstrand, a pioneering geographer known for his work in time geography and spatial analysis.
-
E.
Rasmusen
Rasmusen is a surname, likely a spelling variant of the more common Scandinavian name Rasmussen.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd3fd9c81909bfe95927f7553e3 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.