Triple
T969435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RegioExpress |
E20911
|
entity |
| Predicate | stopPattern |
P8034
|
FINISHED |
| Object | stops mainly at larger intermediate stations |
—
|
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: stops mainly at larger intermediate stations | Statement: [RegioExpress, stopPattern, stops mainly at larger intermediate stations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stopPattern Context triple: [RegioExpress, stopPattern, stops mainly at larger intermediate stations]
-
A.
hasStop
Indicates that something (such as a route, service, or journey) includes or is associated with a particular stop or stopping point.
-
B.
pattern
chosen
Indicates that one entity exhibits, follows, or is characterized by a particular recurring form, structure, or arrangement associated with another entity.
-
C.
isKeyStopOn
Indicates that a particular stop functions as a primary or significant stop along a specified route or service.
-
D.
kitPattern
Indicates the design or visual pattern featured on a team's kit or uniform.
-
E.
reasonForDiscontinuation
Indicates that one entity specifies the cause or justification for stopping, ending, or withdrawing another entity, process, or activity.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4481f508190adcf0a965a23862c |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a579888190afb489ac9fe8391c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.