Triple
T7439904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Östhammar Municipality |
E171719
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Öregrund
Öregrund is a small coastal town in eastern Sweden known for its historic wooden architecture, seaside setting, and role as a popular summer resort.
|
E664839
|
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: Öregrund | Statement: [Östhammar Municipality, contains, Öregrund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Öregrund Context triple: [Östhammar Municipality, contains, Öregrund]
-
A.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
B.
Gruvbyn
Gruvbyn is a historic mining village area on the island of Utö in Sweden, known for its old iron ore mines and traditional archipelago settlement.
-
C.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
D.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
E.
Trollbäcken
Trollbäcken is a residential suburban district in the Stockholm County area of Sweden, known for its proximity to lakes and green spaces.
- 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: Öregrund Triple: [Östhammar Municipality, contains, Öregrund]
Generated description
Öregrund is a small coastal town in eastern Sweden known for its historic wooden architecture, seaside setting, and role as a popular summer resort.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Öregrund Target entity description: Öregrund is a small coastal town in eastern Sweden known for its historic wooden architecture, seaside setting, and role as a popular summer resort.
-
A.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
B.
Gruvbyn
Gruvbyn is a historic mining village area on the island of Utö in Sweden, known for its old iron ore mines and traditional archipelago settlement.
-
C.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
D.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
E.
Trollbäcken
Trollbäcken is a residential suburban district in the Stockholm County area of Sweden, known for its proximity to lakes and green spaces.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34c28648190a426b5d7623b41e8 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c82791ff2c81909967f145d24ff036 |
completed | March 28, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69c828420ebc8190bd124a53de185032 |
completed | March 28, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c828a5c2f88190aedd55d40520c672 |
completed | March 28, 2026, 7:14 p.m. |
Created at: March 27, 2026, 3:13 p.m.