Triple
T20018767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rissa (former municipality) |
E494791
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Skaugdalen
Skaugdalen is a rural valley area in Trøndelag county, Norway, known for its agricultural landscape and small settlements.
|
E1423259
|
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: Skaugdalen | Statement: [Rissa (former municipality), contains, Skaugdalen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skaugdalen Context triple: [Rissa (former municipality), contains, Skaugdalen]
-
A.
Bangdalen
Bangdalen is a small rural settlement located within Namsos municipality in Trøndelag county, Norway.
-
B.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
-
C.
Glåmdalen
Glåmdalen is a valley region in Eastern Norway known for the Glomma River and its surrounding agricultural and forested landscapes.
-
D.
Hallingdal
Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
-
E.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
- 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: Skaugdalen Triple: [Rissa (former municipality), contains, Skaugdalen]
Generated description
Skaugdalen is a rural valley area in Trøndelag county, Norway, known for its agricultural landscape and small settlements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skaugdalen Target entity description: Skaugdalen is a rural valley area in Trøndelag county, Norway, known for its agricultural landscape and small settlements.
-
A.
Bangdalen
Bangdalen is a small rural settlement located within Namsos municipality in Trøndelag county, Norway.
-
B.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
-
C.
Glåmdalen
Glåmdalen is a valley region in Eastern Norway known for the Glomma River and its surrounding agricultural and forested landscapes.
-
D.
Hallingdal
Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
-
E.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623e40748190b1abb0ead9acab4e |
completed | April 20, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a086103b4c4819085616d98a9b4dc84 |
completed | May 16, 2026, 12:20 p.m. |
| NEDg | Description generation | batch_6a0861b954888190a6305aa805aa97ff |
completed | May 16, 2026, 12:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0862237d148190b4e12c878ca9c7a2 |
completed | May 16, 2026, 12:25 p.m. |
Created at: April 11, 2026, 3:34 p.m.