Triple
T15077044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sund municipality |
E380031
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object | Skogsvåg |
E383468
|
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: Skogsvåg | Statement: [Sund municipality, administrativeCentre, Skogsvåg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skogsvåg Context triple: [Sund municipality, administrativeCentre, Skogsvåg]
-
A.
Skogsvåg
chosen
Skogsvåg is a small coastal village in western Norway, located on the island of Sotra in Vestland county.
-
B.
Glåma
Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
-
C.
Tallkrogen
Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
-
D.
Skøyenåsen
Skøyenåsen is a residential neighborhood in Oslo, Norway, known for its green surroundings and access to public transportation.
-
E.
Tjørhomfjellet
Tjørhomfjellet is a ski resort located in Sirdal municipality in southern Norway, known for its alpine slopes and winter sports facilities.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fe5a208190823900b25e298dab |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec878c52c8190bf010b1fd4d21f65 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:03 a.m.