Triple
T6142507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trondheim |
E136993
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Byåsen
Byåsen is a largely residential hillside district in Trondheim, Norway, known for its scenic views over the city and access to outdoor recreation areas.
|
E584446
|
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: Byåsen | Statement: [Trondheim, hasDistrict, Byåsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Byåsen Context triple: [Trondheim, hasDistrict, Byåsen]
-
A.
Nesset
Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
-
B.
Verdalsøra
Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
-
C.
Lærdal
Lærdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscapes, historic wooden architecture, and the UNESCO-listed Nærøyfjord area nearby.
-
D.
Lakselv
Lakselv is a small town in northern Norway that serves as an administrative and transport hub in Finnmark, near the Porsangerfjorden and close to the North Cape region.
-
E.
Orkdalen
Orkdalen is a valley and traditional district in central Norway known for the Orkla River and its agricultural landscapes within Trøndelag county.
- 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: Byåsen Triple: [Trondheim, hasDistrict, Byåsen]
Generated description
Byåsen is a largely residential hillside district in Trondheim, Norway, known for its scenic views over the city and access to outdoor recreation areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Byåsen Target entity description: Byåsen is a largely residential hillside district in Trondheim, Norway, known for its scenic views over the city and access to outdoor recreation areas.
-
A.
Nesset
Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
-
B.
Verdalsøra
Verdalsøra is a small town in Trøndelag county, Norway, known for its riverside setting and role as a local commercial and service hub.
-
C.
Lærdal
Lærdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscapes, historic wooden architecture, and the UNESCO-listed Nærøyfjord area nearby.
-
D.
Lakselv
Lakselv is a small town in northern Norway that serves as an administrative and transport hub in Finnmark, near the Porsangerfjorden and close to the North Cape region.
-
E.
Orkdalen
Orkdalen is a valley and traditional district in central Norway known for the Orkla River and its agricultural landscapes within Trøndelag county.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb387ac8190a60579b59a741425 |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3c26a9c8190a7dfbe0895461d3b |
completed | March 27, 2026, 1:56 a.m. |
| NEDg | Description generation | batch_69c5e6d1d62c81909d1b3fd2adc5ab14 |
completed | March 27, 2026, 2:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c5e73595288190a8c0696d7c1dc887 |
completed | March 27, 2026, 2:11 a.m. |
Created at: March 22, 2026, 4:16 p.m.