Triple
T18113177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lom |
E433531
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Årdal
Årdal is a municipality in Vestland county, Norway, known for its hydroelectric power production, aluminum industry, and scenic fjord and mountain landscapes.
|
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, borders, Årdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Årdal Context triple: [Lom, borders, Årdal]
-
A.
Årdal
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
-
B.
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.
-
C.
Naustdal
Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
-
D.
Sunndal
Sunndal is a municipality in Møre og Romsdal county in western Norway, known for its dramatic fjord landscape and significant aluminum industry.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- 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, borders, Årdal]
Generated description
Årdal is a municipality in Vestland county, Norway, known for its hydroelectric power production, aluminum industry, and scenic fjord and mountain landscapes.
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 hydroelectric power production, aluminum industry, and scenic fjord and mountain landscapes.
-
A.
Årdal
chosen
Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
-
B.
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.
-
C.
Naustdal
Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
-
D.
Sunndal
Sunndal is a municipality in Møre og Romsdal county in western Norway, known for its dramatic fjord landscape and significant aluminum industry.
-
E.
Verdal
Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
- F. None of above.
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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd3fd9c81909bfe95927f7553e3 |
completed | April 19, 2026, 1:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03ac58c3ec8190b72fc6ff1cac67e4 |
completed | May 12, 2026, 10:40 p.m. |
| NEDg | Description generation | batch_6a03ace9a6d48190ac0504903e08ba8b |
completed | May 12, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03ad7bd4708190904a316f87b80664 |
completed | May 12, 2026, 10:45 p.m. |
Created at: April 10, 2026, 10:28 a.m.