Triple
T6266765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lom, Norway |
E140432
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Årdal
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
|
E666044
|
NE FINISHED |
How this triple was built (4 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: Årdal | Statement: [Lom, Norway, borders, Årdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Årdal Context triple: [Lom, Norway, borders, Årdal]
-
A.
Øvre Årdal
Øvre Årdal is a small industrial village in Vestland county, Norway, known as a gateway to the Jotunheimen mountain area and its popular hiking routes.
-
B.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
C.
Sunndalsøra
Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
-
D.
Alvdal
Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
-
E.
Årvoll
Årvoll is a residential neighborhood in Oslo, Norway, known for its proximity to Lillomarka forest and a mix of apartment blocks and low-rise housing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Årdal Triple: [Lom, Norway, borders, Årdal]
Generated description
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Årdal Target entity description: Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
-
A.
Øvre Årdal
Øvre Årdal is a small industrial village in Vestland county, Norway, known as a gateway to the Jotunheimen mountain area and its popular hiking routes.
-
B.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
-
C.
Sunndalsøra
Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
-
D.
Alvdal
Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
-
E.
Årvoll
Årvoll is a residential neighborhood in Oslo, Norway, known for its proximity to Lillomarka forest and a mix of apartment blocks and low-rise housing.
- F. None of above. chosen
Provenance (5 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0639fdad081908492c44d369df8c5 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83414c374819085ca1e441728c6af |
completed | March 28, 2026, 8:03 p.m. |
| NEDg | Description generation | batch_69c834df98908190a13df51182751a75 |
completed | March 28, 2026, 8:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83597d0f0819091a095e8376fd644 |
completed | March 28, 2026, 8:10 p.m. |
Created at: March 22, 2026, 4:25 p.m.