Triple
T3556528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordfjord |
E75232
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Stryn
Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
|
E375474
|
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: Stryn | Statement: [Nordfjord, hasPart, Stryn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stryn Context triple: [Nordfjord, hasPart, Stryn]
-
A.
Finnsnes
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
B.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
C.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
D.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
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: Stryn Triple: [Nordfjord, hasPart, Stryn]
Generated description
Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stryn Target entity description: Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
-
A.
Finnsnes
Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
-
B.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
C.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
D.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
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
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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc057cc788190a6c4f3781f43abce |
completed | March 8, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44ef0a4588190b82a395760c8072a |
completed | March 13, 2026, 5:52 p.m. |
| NEDg | Description generation | batch_69b4536c7db88190bd9d8fb5898fb0d9 |
completed | March 13, 2026, 6:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b45edec6e48190aaed2fb4fee2dcb5 |
completed | March 13, 2026, 7 p.m. |
Created at: March 8, 2026, 3:20 p.m.