Triple
T15360384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sykkylven |
E367273
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object |
Aure sentrum
Aure sentrum is the main village and commercial hub of the Sykkylven municipality in Møre og Romsdal county, Norway.
|
E1153640
|
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: Aure sentrum | Statement: [Sykkylven, administrativeCenter, Aure sentrum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aure sentrum Context triple: [Sykkylven, administrativeCenter, Aure sentrum]
-
A.
Sentrum
Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
-
B.
Aulestad
Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
-
C.
Akure
Akure is the capital city of Ondo State in southwestern Nigeria, known as an important administrative and commercial center in the region.
-
D.
Aujon
Aujon is a river in northeastern France that flows through the Haute-Marne department.
-
E.
Aursunden
Aursunden is a large lake in Røros municipality in Trøndelag county, Norway, known for its scenic surroundings and role in regional hydrology.
- 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: Aure sentrum Triple: [Sykkylven, administrativeCenter, Aure sentrum]
Generated description
Aure sentrum is the main village and commercial hub of the Sykkylven municipality in Møre og Romsdal county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aure sentrum Target entity description: Aure sentrum is the main village and commercial hub of the Sykkylven municipality in Møre og Romsdal county, Norway.
-
A.
Sentrum
Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
-
B.
Aulestad
Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
-
C.
Akure
Akure is the capital city of Ondo State in southwestern Nigeria, known as an important administrative and commercial center in the region.
-
D.
Aujon
Aujon is a river in northeastern France that flows through the Haute-Marne department.
-
E.
Aursunden
Aursunden is a large lake in Røros municipality in Trøndelag county, Norway, known for its scenic surroundings and role in regional hydrology.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b4a181c8190bffc1ac1a86e215d |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0f82441c81909a8ae13817fd3e96 |
completed | May 9, 2026, 10:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0fd586708190a54b33efd27d84b2 |
completed | May 9, 2026, 10:43 a.m. |
Created at: April 10, 2026, 3:18 a.m.