Triple
T6339997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nykvarn Municipality |
E142600
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object |
Nykvarn
Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
|
E587389
|
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: Nykvarn | Statement: [Nykvarn Municipality, seat, Nykvarn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nykvarn Context triple: [Nykvarn Municipality, seat, Nykvarn]
-
A.
Svalöv
Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
D.
Kyrkslätt
Kyrkslätt is the Swedish name for Kirkkonummi, a coastal municipality in southern Finland located just west of Helsinki.
-
E.
Hudiksvall
Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
- 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: Nykvarn Triple: [Nykvarn Municipality, seat, Nykvarn]
Generated description
Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nykvarn Target entity description: Nykvarn is a small locality in eastern Sweden that serves as the administrative and population center of Nykvarn Municipality in Stockholm County.
-
A.
Svalöv
Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
-
B.
Strängnäs
Strängnäs is a historic Swedish town known for its medieval cathedral and picturesque location on the shores of Lake Mälaren.
-
C.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
D.
Kyrkslätt
Kyrkslätt is the Swedish name for Kirkkonummi, a coastal municipality in southern Finland located just west of Helsinki.
-
E.
Hudiksvall
Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
- 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_69c008d5ab108190b346c465696824a9 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06741fbbc81908d947182b197bf59 |
completed | March 22, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c604352f148190b5accc28462256ad |
completed | March 27, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69c620db73dc8190b9e75e0a9d01ff5a |
completed | March 27, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c624e2b3c081908e5c05da38121631 |
completed | March 27, 2026, 6:34 a.m. |
Created at: March 22, 2026, 4:30 p.m.