Triple
T26315659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rüsselsheim Opelwerk station |
E661964
|
entity |
| Predicate | usedForShiftTraffic |
P168056
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Rüsselsheim Opelwerk station, usedForShiftTraffic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForShiftTraffic Context triple: [Rüsselsheim Opelwerk station, usedForShiftTraffic, yes]
-
A.
rightOfWayUsedFor
Indicates that a particular right of way is utilized for a specific purpose, activity, or type of use.
-
B.
relievesTrafficFrom
Indicates that one entity reduces or alleviates traffic congestion that would otherwise occur on another entity.
-
C.
secondaryTraffic
Indicates that there is an additional, indirect, or subordinate flow of traffic associated with a primary traffic stream or event.
-
D.
roadUse
Indicates that an entity utilizes or travels on a particular road or roadway for movement or transport.
-
E.
usedTransportationInfrastructure
Indicates that an entity made use of some form of transportation infrastructure (such as roads, railways, or ports) to enable movement or transit.
- F. None of above. chosen
Provenance (4 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 26, 2026, 10:24 p.m.