Triple
T20202661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hagaparken |
E493262
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Haga Brunnsvik
Haga Brunnsvik is a scenic lakeside area within Stockholm’s Hagaparken, known for its tranquil natural setting and waterfront views.
|
E1422874
|
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: Haga Brunnsvik | Statement: [Hagaparken, hasAttraction, Haga Brunnsvik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haga Brunnsvik Context triple: [Hagaparken, hasAttraction, Haga Brunnsvik]
-
A.
Svingvoll
Svingvoll is a small village in Innlandet county, Norway, known for its rural setting and proximity to skiing and outdoor recreation areas.
-
B.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
C.
Vålebru
Vålebru is a village in Innlandet county, Norway, serving as the main local hub for services and administration in Ringebu municipality.
-
D.
Torsbjørka
Torsbjørka is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
-
E.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
- 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: Haga Brunnsvik Triple: [Hagaparken, hasAttraction, Haga Brunnsvik]
Generated description
Haga Brunnsvik is a scenic lakeside area within Stockholm’s Hagaparken, known for its tranquil natural setting and waterfront views.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haga Brunnsvik Target entity description: Haga Brunnsvik is a scenic lakeside area within Stockholm’s Hagaparken, known for its tranquil natural setting and waterfront views.
-
A.
Svingvoll
Svingvoll is a small village in Innlandet county, Norway, known for its rural setting and proximity to skiing and outdoor recreation areas.
-
B.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
C.
Vålebru
Vålebru is a village in Innlandet county, Norway, serving as the main local hub for services and administration in Ringebu municipality.
-
D.
Torsbjørka
Torsbjørka is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
-
E.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d8ec73c8190b630599c5ceb22ac |
completed | April 20, 2026, 6:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a085a13ad708190bcbc91babdc4085b |
completed | May 16, 2026, 11:50 a.m. |
| NEDg | Description generation | batch_6a085c72c81c8190bbe3c42b5832900c |
completed | May 16, 2026, noon |
| NED2 | Entity disambiguation (via description) | batch_6a085cea59008190904995df11f6578d |
completed | May 16, 2026, 12:02 p.m. |
Created at: April 11, 2026, 11:37 p.m.