Triple
T33483519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schkeuditzer Kreuz |
E857544
|
entity |
| Predicate | hasRoadDirection |
P4069
|
FINISHED |
| Object | north–south via A9 |
—
|
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: north–south via A9 | Statement: [Schkeuditzer Kreuz, hasRoadDirection, north–south via A9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadDirection Context triple: [Schkeuditzer Kreuz, hasRoadDirection, north–south via A9]
-
A.
hasStreetDirection
Indicates that a street or road segment is associated with a specific directional orientation (e.g., northbound, east-west).
-
B.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
C.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
D.
hasTrafficDirection
chosen
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
E.
roadDirectionConvention
Indicates the customary rule in a place for which side of the road vehicles are expected to drive on.
- 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_69f3497547608190a1a0f2365fb713ee |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdfbafe32081909c62653ff4fc155c |
completed | May 8, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69fdf64db4a881908f8250e24ae3cefb |
completed | May 8, 2026, 2:42 p.m. |
Created at: May 1, 2026, 1:38 a.m.