Triple
T13710705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Växjö |
E328762
|
entity |
| Predicate | hasStadium |
P105
|
FINISHED |
| Object |
Visma Arena
Visma Arena is a multi-purpose sports stadium in Växjö, Sweden, primarily used for football matches and home to local professional teams.
|
E1056559
|
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: Visma Arena | Statement: [Växjö, hasStadium, Visma Arena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Visma Arena Context triple: [Växjö, hasStadium, Visma Arena]
-
A.
Skagerak Arena
Skagerak Arena is a football stadium in Skien, Norway, best known as the home ground of the club Odds BK.
-
B.
Scandinavium arena
Scandinavium arena is a major indoor sports and entertainment venue in Gothenburg, Sweden, known for hosting ice hockey, concerts, and international events.
-
C.
Ballerup Super Arena
Ballerup Super Arena is a large indoor velodrome and multi-purpose sports and events venue located in Ballerup, Denmark.
-
D.
ESPRIT Arena
ESPRIT Arena is a modern multi-purpose stadium in Düsseldorf, Germany, primarily used for football matches and large-scale events.
-
E.
Royal Arena
Royal Arena is a modern multi-purpose indoor arena in Copenhagen, Denmark, known for hosting major international sports events and concerts.
- 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: Visma Arena Triple: [Växjö, hasStadium, Visma Arena]
Generated description
Visma Arena is a multi-purpose sports stadium in Växjö, Sweden, primarily used for football matches and home to local professional teams.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Visma Arena Target entity description: Visma Arena is a multi-purpose sports stadium in Växjö, Sweden, primarily used for football matches and home to local professional teams.
-
A.
Skagerak Arena
Skagerak Arena is a football stadium in Skien, Norway, best known as the home ground of the club Odds BK.
-
B.
Scandinavium arena
Scandinavium arena is a major indoor sports and entertainment venue in Gothenburg, Sweden, known for hosting ice hockey, concerts, and international events.
-
C.
Ballerup Super Arena
Ballerup Super Arena is a large indoor velodrome and multi-purpose sports and events venue located in Ballerup, Denmark.
-
D.
ESPRIT Arena
ESPRIT Arena is a modern multi-purpose stadium in Düsseldorf, Germany, primarily used for football matches and large-scale events.
-
E.
Royal Arena
Royal Arena is a modern multi-purpose indoor arena in Copenhagen, Denmark, known for hosting major international sports events and concerts.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd43949e6c8190ae5e4fa119cde33a |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d54a68081908df25edf6d5df362 |
completed | May 3, 2026, 7:09 p.m. |
| NEDg | Description generation | batch_69f79e1a90408190936cb71e567e10aa |
completed | May 3, 2026, 7:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f79ee74ea48190a4c753b12bb9190e |
completed | May 3, 2026, 7:15 p.m. |
Created at: April 9, 2026, 9:54 p.m.