Triple
T15030306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skärholmen |
E378324
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object |
Bredäng
Bredäng is a residential district in southwestern Stockholm, Sweden, known for its 1960s apartment blocks, green areas, and proximity to Lake Mälaren.
|
E1134378
|
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: Bredäng | Statement: [Skärholmen, hasNeighbourhood, Bredäng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bredäng Context triple: [Skärholmen, hasNeighbourhood, Bredäng]
-
A.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
B.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Såtenäs
Såtenäs is a locality in western Sweden best known as a major Swedish Air Force base and home of the F 7 Wing.
-
E.
Kungsbacka
Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
- 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: Bredäng Triple: [Skärholmen, hasNeighbourhood, Bredäng]
Generated description
Bredäng is a residential district in southwestern Stockholm, Sweden, known for its 1960s apartment blocks, green areas, and proximity to Lake Mälaren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bredäng Target entity description: Bredäng is a residential district in southwestern Stockholm, Sweden, known for its 1960s apartment blocks, green areas, and proximity to Lake Mälaren.
-
A.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
-
B.
Korsnäs
Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
-
C.
Bollnäs
Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
-
D.
Såtenäs
Såtenäs is a locality in western Sweden best known as a major Swedish Air Force base and home of the F 7 Wing.
-
E.
Kungsbacka
Kungsbacka is a town in southwestern Sweden known for its coastal location, historic wooden center, and role as a commuter hub for nearby Gothenburg.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9ddb46888190b1d2fe2992fc120b |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9efce5dc8190909b891c476d5291 |
completed | May 9, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea2bd5d2c8190b26d2393cd8abb3e |
completed | May 9, 2026, 2:58 a.m. |
Created at: April 10, 2026, 2:59 a.m.