Triple
T4075496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankenderby |
E86754
|
entity |
| Predicate | traditionalDerbyBetween |
P52081
|
FINISHED |
| Object | Franconian clubs |
—
|
LITERAL 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: Franconian clubs | Statement: [Frankenderby, traditionalDerbyBetween, Franconian clubs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalDerbyBetween Context triple: [Frankenderby, traditionalDerbyBetween, Franconian clubs]
-
A.
cityDerby
Indicates a competitive or rivalry relationship between two cities, often in sports or similar local contests.
-
B.
playsInDerbyWith
Indicates that two entities participate together as opponents or competitors in the same derby event or match.
-
C.
playsInDerby
Indicates participation by an entity as a competitor or performer in a derby event.
-
D.
regionDerby
chosen
Indicates a competitive match or rivalry that takes place between teams or participants from the same geographic region.
-
E.
notableRivalry
Indicates a significant, well-recognized competitive or adversarial relationship between two entities.
- F. None of above.
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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc25e2e08190b3c048e1b8f85bbf |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.