Triple
T30557625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FV Biebrich 02 |
E777742
|
entity |
| Predicate | hasLocalRivalriesRegion |
P80695
|
FINISHED |
| Object | Wiesbaden area |
—
|
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: Wiesbaden area | Statement: [FV Biebrich 02, hasLocalRivalriesRegion, Wiesbaden area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalRivalriesRegion Context triple: [FV Biebrich 02, hasLocalRivalriesRegion, Wiesbaden area]
-
A.
hasLocalRivalry
Indicates that there is an ongoing competitive or adversarial relationship between entities that are geographically close or share the same local area.
-
B.
rivalryRegion
chosen
Indicates a competitive or adversarial relationship that exists between entities within a specific geographic or regional context.
-
C.
hasRivalryIn
Indicates that two entities are in a state of competition or opposition within a specific domain, context, or field.
-
D.
hasLocalRivalryVenueWith
Indicates that two entities share a venue or location where a local rivalry between them is regularly contested or expressed.
-
E.
hasInStateRivalries
Indicates that two entities are rivals or competitors within the same state or internal jurisdiction.
- 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_69f2249ed41c8190b175170ecfd6e1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 29, 2026, 8:21 p.m.