Triple
T14818744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ørestad |
E348386
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Royal Arena |
E921808
|
NE FINISHED |
How this triple was built (2 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: Royal Arena | Statement: [Ørestad, hasLandmark, Royal Arena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Royal Arena Context triple: [Ørestad, hasLandmark, Royal Arena]
-
A.
Royal Arena
chosen
Royal Arena is a modern multi-purpose indoor arena in Copenhagen, Denmark, known for hosting major international sports events and concerts.
-
B.
Skagerak Arena
Skagerak Arena is a football stadium in Skien, Norway, best known as the home ground of the club Odds BK.
-
C.
ESPRIT Arena
ESPRIT Arena is a modern multi-purpose stadium in Düsseldorf, Germany, primarily used for football matches and large-scale events.
-
D.
AXA Arena
AXA Arena is a multi-purpose indoor ice hockey arena in Södertälje, Sweden, best known as the home venue of the Södertälje SK ice hockey team.
-
E.
Visma Arena
Visma Arena is a multi-purpose sports stadium in Växjö, Sweden, primarily used for football matches and home to local professional teams.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe4cf38819090f25ef045351d5d |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64f8b4148190bc24f9a307178419 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:50 a.m.