Triple
T11194494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweden national football team |
E264885
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Blågult |
E559464
|
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: Blågult | Statement: [Sweden national football team, nickname, Blågult]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blågult Context triple: [Sweden national football team, nickname, Blågult]
-
A.
Blågult
chosen
Blågult is the popular Swedish nickname for the Sweden women's national football team, referencing the country's blue and yellow colors.
-
B.
Blå
Blå is a renowned live music and cultural venue in Oslo, Norway, known for its vibrant jazz, electronic, and alternative music scene.
-
C.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
D.
Blåvitt
Blåvitt is the popular nickname of IFK Göteborg, one of Sweden’s most successful and historically significant football clubs.
-
E.
Geel
Geel is a city in the Flemish region of Belgium, noted for its long-standing tradition of community-based psychiatric care.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8bf14e481908563b15790af4d20 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e483f8ecf4819086f0bab3ca9ddcb4 |
completed | April 19, 2026, 7:27 a.m. |
Created at: April 8, 2026, 9:29 p.m.