Triple
T7786260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enköping |
E187251
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object |
Drömparken
Drömparken is a well-known public garden in Enköping, Sweden, celebrated for its lush perennial plantings and inspirational landscape design.
|
E692771
|
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: Drömparken | Statement: [Enköping, hasPark, Drömparken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drömparken Context triple: [Enköping, hasPark, Drömparken]
-
A.
Gärdet
Gärdet is a large open parkland and residential area in central Stockholm, known for its green spaces, outdoor activities, and functionalist-era architecture.
-
B.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
C.
Runhällen
Runhällen is a small locality in central Sweden situated within Heby Municipality in Uppsala County.
-
D.
Slumber Mountain
Slumber Mountain is a fictional, remote wilderness peak featured as the eerie and mysterious backdrop in the early fantasy film "The Ghost of Slumber Mountain."
-
E.
Mo i Rana
Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
- 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: Drömparken Triple: [Enköping, hasPark, Drömparken]
Generated description
Drömparken is a well-known public garden in Enköping, Sweden, celebrated for its lush perennial plantings and inspirational landscape design.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Drömparken Target entity description: Drömparken is a well-known public garden in Enköping, Sweden, celebrated for its lush perennial plantings and inspirational landscape design.
-
A.
Gärdet
Gärdet is a large open parkland and residential area in central Stockholm, known for its green spaces, outdoor activities, and functionalist-era architecture.
-
B.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
C.
Runhällen
Runhällen is a small locality in central Sweden situated within Heby Municipality in Uppsala County.
-
D.
Slumber Mountain
Slumber Mountain is a fictional, remote wilderness peak featured as the eerie and mysterious backdrop in the early fantasy film "The Ghost of Slumber Mountain."
-
E.
Mo i Rana
Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf2462248190863f838f0e077923 |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf6123ad48190a50339073e91748c |
completed | March 30, 2026, 10:15 p.m. |
| NEDg | Description generation | batch_69caf81ff934819094f8089b0bd8dde7 |
completed | March 30, 2026, 10:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cafa512e748190a52fe462d3d59f06 |
completed | March 30, 2026, 10:33 p.m. |
Created at: March 30, 2026, 4:23 p.m.