Triple
T20850255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamla Ullevi |
E513337
|
entity |
| Predicate | hasTenant |
P3277
|
FINISHED |
| Object | Örgryte IS |
—
|
NE NERFINISHED |
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: Örgryte IS | Statement: [Gamla Ullevi, hasTenant, Örgryte IS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Örgryte IS Context triple: [Gamla Ullevi, hasTenant, Örgryte IS]
-
A.
Örgryte IS
chosen
Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
-
B.
Örebro SK
Örebro SK is a Swedish professional sports club best known for its football team, which competes in the national league system.
-
C.
IFK Östersund
IFK Östersund is a Swedish football club from Östersund, known locally for its traditional status and rivalry with Östersunds FK.
-
D.
Örnsköldsviks SK
Örnsköldsviks SK is a Swedish sports club based in Örnsköldsvik, known for organizing and promoting local athletic activities and teams.
-
E.
Djurgården
Djurgården is a central Stockholm island known for its parks, museums, and major attractions like the Vasa Museum and Skansen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c352ca8c819094545dbe67bfe3dc |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.