Triple
T16726770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankfurter Kreuz |
E406482
|
entity |
| Predicate | hasFlyoverRamps |
P119068
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Frankfurter Kreuz, hasFlyoverRamps, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlyoverRamps Context triple: [Frankfurter Kreuz, hasFlyoverRamps, true]
-
A.
containsRamps
chosen
Indicates that one entity includes or is equipped with one or more ramps as part of its structure or features.
-
B.
hasNumberOfSlipRoads
Indicates the number of slip roads (on/off ramps) associated with a particular road segment or junction.
-
C.
hasBridgeUnderpasses
Indicates that one structure, typically a bridge, includes or provides underpasses that allow passage beneath it.
-
D.
hasGradeSeparatedInterchanges
Indicates that the route or roadway includes interchanges where traffic flows are separated by different levels (e.g., overpasses/underpasses) rather than intersecting at the same grade.
-
E.
hasFreewaySegments
Indicates that one entity includes, contains, or is associated with specific freeway segments as part of its structure or network.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38748f538819097de1fdee9b42f34 |
completed | April 18, 2026, 1:29 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.