Triple
T13092612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitesse Arnhem |
E310498
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Geel-zwarten |
E371453
|
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: Geel-zwarten | Statement: [Vitesse Arnhem, nickname, Geel-zwarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geel-zwarten Context triple: [Vitesse Arnhem, nickname, Geel-zwarten]
-
A.
Geel-zwarten
chosen
Geel-zwarten is a common Dutch nickname referring to the football club Vitesse, derived from the team’s yellow-and-black colors.
-
B.
Rood-witten
Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
-
C.
Black and Yellow
"Black and Yellow" is a 2010 hip-hop single by Wiz Khalifa that became a major commercial hit and an anthem associated with the city of Pittsburgh.
-
D.
Black-and-Red
Black-and-Red is the widely used nickname for Major League Soccer club D.C. United, referencing the team’s traditional colors and identity.
-
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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9813acbac8190b2fe5e07287457cf |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d61629ac8190a2dfa11951a877f0 |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:03 p.m.