Triple
T15663455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sogndal |
E376625
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Lærdal |
E385170
|
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: Lærdal | Statement: [Sogndal, borders, Lærdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lærdal Context triple: [Sogndal, borders, Lærdal]
-
A.
Lærdal
chosen
Lærdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscapes, historic wooden architecture, and the UNESCO-listed Nærøyfjord area nearby.
-
B.
Groruddalen
Groruddalen is a large valley and suburban area in the northeastern part of Oslo, Norway, known for its diverse population and extensive residential neighborhoods.
-
C.
Gravdal
Gravdal is a small coastal village on the island of Vestvågøy in Norway’s Lofoten archipelago.
-
D.
Brumunddal
Brumunddal is a town in Ringsaker Municipality in Innlandet county, Norway, known as an administrative and commercial center on the eastern shore of Lake Mjøsa.
-
E.
Glåma
Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0e2668819092e52712cddd0721 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb7c2a6081908e957d39ec056062 |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:16 a.m.