Triple
T17339253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdal Tunnel |
E421020
|
entity |
| Predicate | hasOfficialNameInNorwegian |
P24264
|
FINISHED |
| Object | Lærdalstunnelen |
E421020
|
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: Lærdalstunnelen | Statement: [Lærdal Tunnel, hasOfficialNameInNorwegian, Lærdalstunnelen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lærdalstunnelen Context triple: [Lærdal Tunnel, hasOfficialNameInNorwegian, Lærdalstunnelen]
-
A.
Lærdal Tunnel
chosen
The Lærdal Tunnel is a 24.5-kilometer road tunnel in Norway, renowned as one of the world's longest road tunnels and a key link between Oslo and Bergen.
-
B.
Strynefjell Tunnel
Strynefjell Tunnel is a road tunnel in Norway that carries traffic through the mountainous Strynefjell area along a key east–west route.
-
C.
Honningsvåg Tunnel
Honningsvåg Tunnel is a road tunnel in northern Norway that carries traffic along the E69 highway toward the North Cape.
-
D.
Karmøytunnelen
Karmøytunnelen is an undersea road tunnel in Rogaland county, Norway, connecting the island of Karmøy to the mainland as part of the regional road network.
-
E.
Oslo Tunnel
The Oslo Tunnel is a central railway tunnel in Oslo, Norway, that carries most of the city's mainline train traffic between its principal stations.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c56c8148190ab6e3e2eff09725e |
completed | May 11, 2026, 7:59 a.m. |
Created at: April 10, 2026, 5:44 a.m.