Triple
T15073412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stureplan |
E379937
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Svampen
Svampen is a distinctive mushroom-shaped concrete canopy and popular meeting point located in Stockholm’s Stureplan square.
|
E1134786
|
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: Svampen | Statement: [Stureplan, hasLandmark, Svampen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Svampen Context triple: [Stureplan, hasLandmark, Svampen]
-
A.
Svarttinden
Svarttinden is a mountain peak that forms the highest point on the island of Gimsøya in Norway’s Lofoten archipelago.
-
B.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
C.
Steinsåsen
Steinsåsen is a small village in Hole Municipality in Viken county, Norway, situated near the Tyrifjorden lake and known for its scenic rural surroundings.
-
D.
Grødem
Grødem is a coastal village in Randaberg municipality in Rogaland county, Norway, known for its residential areas and proximity to the city of Stavanger.
-
E.
Storvreten
Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
- 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: Svampen Triple: [Stureplan, hasLandmark, Svampen]
Generated description
Svampen is a distinctive mushroom-shaped concrete canopy and popular meeting point located in Stockholm’s Stureplan square.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Svampen Target entity description: Svampen is a distinctive mushroom-shaped concrete canopy and popular meeting point located in Stockholm’s Stureplan square.
-
A.
Svarttinden
Svarttinden is a mountain peak that forms the highest point on the island of Gimsøya in Norway’s Lofoten archipelago.
-
B.
Blåränderna
Blåränderna is a popular nickname for Djurgårdens IF, referring to the Swedish sports club’s iconic blue-striped team colors.
-
C.
Steinsåsen
Steinsåsen is a small village in Hole Municipality in Viken county, Norway, situated near the Tyrifjorden lake and known for its scenic rural surroundings.
-
D.
Grødem
Grødem is a coastal village in Randaberg municipality in Rogaland county, Norway, known for its residential areas and proximity to the city of Stavanger.
-
E.
Storvreten
Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fa0570819088a97b28173154cd |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5cff69c8190b6252509c1aa7ebb |
completed | May 9, 2026, 3:11 a.m. |
| NEDg | Description generation | batch_69fea6bf2558819082fc91fe8df6f3f5 |
completed | May 9, 2026, 3:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea8018a088190b6eba72a7e6196b2 |
completed | May 9, 2026, 3:20 a.m. |
Created at: April 10, 2026, 3:02 a.m.