Triple
T10628656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Östersund Municipality |
E250390
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Tandsbyn
Tandsbyn is a small locality in Jämtland County, Sweden, situated within the rural surroundings south of the city of Östersund.
|
E875720
|
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: Tandsbyn | Statement: [Östersund Municipality, hasSettlement, Tandsbyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tandsbyn Context triple: [Östersund Municipality, hasSettlement, Tandsbyn]
-
A.
Tantolunden
Tantolunden is a large park and recreational area in Stockholm known for its allotment gardens, waterfront, and outdoor activities.
-
B.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
C.
Edsbyn
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
-
D.
Tynningö
Tynningö is an island in Sweden’s Stockholm archipelago, known for its summer homes, natural scenery, and proximity to the town of Vaxholm.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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: Tandsbyn Triple: [Östersund Municipality, hasSettlement, Tandsbyn]
Generated description
Tandsbyn is a small locality in Jämtland County, Sweden, situated within the rural surroundings south of the city of Östersund.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tandsbyn Target entity description: Tandsbyn is a small locality in Jämtland County, Sweden, situated within the rural surroundings south of the city of Östersund.
-
A.
Tantolunden
Tantolunden is a large park and recreational area in Stockholm known for its allotment gardens, waterfront, and outdoor activities.
-
B.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
C.
Edsbyn
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
-
D.
Tynningö
Tynningö is an island in Sweden’s Stockholm archipelago, known for its summer homes, natural scenery, and proximity to the town of Vaxholm.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df9228088190bdd57a95d8671618 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96babc290819096c0c914d038ba01 |
completed | April 10, 2026, 9:29 p.m. |
| NEDg | Description generation | batch_69d96def8bfc81909d6a5addf724691b |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d96fedb18881908570593856f4aade |
completed | April 10, 2026, 9:47 p.m. |
Created at: April 8, 2026, 8:59 p.m.