Triple
T16182253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Målselva |
E392712
|
entity |
| Predicate | mainSourceRegion |
P410
|
FINISHED |
| Object |
Rostadalen
Rostadalen is a scenic valley in Troms, Northern Norway, known for its rivers, mountains, and outdoor recreation opportunities such as hiking, skiing, and fishing.
|
E1201168
|
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: Rostadalen | Statement: [Målselva, mainSourceRegion, Rostadalen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rostadalen Context triple: [Målselva, mainSourceRegion, Rostadalen]
-
A.
Svarstad
Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
-
B.
Storå
Storå is a small coastal settlement located on the shores of the fjord in the former municipality of Tysfjord in Nordland county, Norway.
-
C.
Storå
Storå is a river in western Jutland, Denmark, known for flowing through the town of Holstebro and contributing to the region’s natural and cultural landscape.
-
D.
Bålsta
Bålsta is a locality in Uppsala County, Sweden, known as the main urban center of Håbo Municipality and a commuter town within the Greater Stockholm region.
-
E.
Meråker
Meråker is a mountainous municipality in Trøndelag county, Norway, known for its outdoor recreation, skiing facilities, and proximity to the Swedish border.
- 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: Rostadalen Triple: [Målselva, mainSourceRegion, Rostadalen]
Generated description
Rostadalen is a scenic valley in Troms, Northern Norway, known for its rivers, mountains, and outdoor recreation opportunities such as hiking, skiing, and fishing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rostadalen Target entity description: Rostadalen is a scenic valley in Troms, Northern Norway, known for its rivers, mountains, and outdoor recreation opportunities such as hiking, skiing, and fishing.
-
A.
Svarstad
Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
-
B.
Storå
Storå is a small coastal settlement located on the shores of the fjord in the former municipality of Tysfjord in Nordland county, Norway.
-
C.
Storå
Storå is a river in western Jutland, Denmark, known for flowing through the town of Holstebro and contributing to the region’s natural and cultural landscape.
-
D.
Bålsta
Bålsta is a locality in Uppsala County, Sweden, known as the main urban center of Håbo Municipality and a commuter town within the Greater Stockholm region.
-
E.
Meråker
Meråker is a mountainous municipality in Trøndelag county, Norway, known for its outdoor recreation, skiing facilities, and proximity to the Swedish border.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205d858c8190802d44e08e3cdcd6 |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007899b408190abcb7e72bdc81e9d |
completed | May 10, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_6a000900bfbc8190b21eb513838759a9 |
completed | May 10, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a000a0fc93c819088d9233aaa5e2017 |
completed | May 10, 2026, 4:31 a.m. |
Created at: April 10, 2026, 5:02 a.m.