Triple
T15360103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aksla viewpoint |
E367266
|
entity |
| Predicate | hasView |
P854
|
FINISHED |
| Object | Ålesund town center |
E74923
|
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: Ålesund town center | Statement: [Aksla viewpoint, hasView, Ålesund town center]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ålesund town center Context triple: [Aksla viewpoint, hasView, Ålesund town center]
-
A.
Ålesund
chosen
Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
-
B.
Ålesund Municipality
Ålesund Municipality is a local government area in Møre og Romsdal county, Norway, encompassing the coastal city of Ålesund and its surrounding islands.
-
C.
Marstrand
Marstrand is a historic seaside town and popular sailing destination on Sweden’s west coast, known for its fortress and picturesque archipelago setting.
-
D.
Stavanger
Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
-
E.
Egersund
Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cec4f2481908fae5209bfd48dcf |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:18 a.m.