Triple
T1481869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tøyen |
E30974
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Tøyenbadet
Tøyenbadet is a major public swimming facility in Oslo, Norway, known for its indoor and outdoor pools and recreational amenities.
|
E169378
|
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: Tøyenbadet | Statement: [Tøyen, hasLandmark, Tøyenbadet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tøyenbadet Context triple: [Tøyen, hasLandmark, Tøyenbadet]
-
A.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
B.
Kongsseteren
Kongsseteren is a historic winter residence and retreat used by the Norwegian royal family near Oslo.
-
C.
Frognerseteren
Frognerseteren is a hilltop area in Oslo, Norway, known for its panoramic views over the city, traditional wooden restaurant, and access to popular hiking and skiing trails.
-
D.
Ringen via Tøyen
Ringen via Tøyen is a circular service pattern on the Oslo Metro that routes trains through Tøyen station before completing a loop.
-
E.
Kagerplassen
Kagerplassen is a lake and recreational water area in South Holland, Netherlands, popular for boating, sailing, and watersports amid a landscape of polders and windmills.
- 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: Tøyenbadet Triple: [Tøyen, hasLandmark, Tøyenbadet]
Generated description
Tøyenbadet is a major public swimming facility in Oslo, Norway, known for its indoor and outdoor pools and recreational amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tøyenbadet Target entity description: Tøyenbadet is a major public swimming facility in Oslo, Norway, known for its indoor and outdoor pools and recreational amenities.
-
A.
Tøyen
Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
-
B.
Kongsseteren
Kongsseteren is a historic winter residence and retreat used by the Norwegian royal family near Oslo.
-
C.
Frognerseteren
Frognerseteren is a hilltop area in Oslo, Norway, known for its panoramic views over the city, traditional wooden restaurant, and access to popular hiking and skiing trails.
-
D.
Ringen via Tøyen
Ringen via Tøyen is a circular service pattern on the Oslo Metro that routes trains through Tøyen station before completing a loop.
-
E.
Kagerplassen
Kagerplassen is a lake and recreational water area in South Holland, Netherlands, popular for boating, sailing, and watersports amid a landscape of polders and windmills.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c6782f088190930d25a56161e2b3 |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15b1bea08190a1e21ddc15148d3a |
completed | March 8, 2026, 6:22 a.m. |
| NEDg | Description generation | batch_69ad1694bcc48190bf54dca4479a95e7 |
completed | March 8, 2026, 6:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad170694f48190840f08db72d9f315 |
completed | March 8, 2026, 6:28 a.m. |
Created at: March 1, 2026, 8:11 p.m.