Triple
T29773002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braunschweig tram network |
E755297
|
entity |
| Predicate | usesTrafficSide |
P4069
|
FINISHED |
| Object | right-hand running |
—
|
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: right-hand running | Statement: [Braunschweig tram network, usesTrafficSide, right-hand running]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrafficSide Context triple: [Braunschweig tram network, usesTrafficSide, right-hand running]
-
A.
hasTrafficDirection
chosen
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
B.
supportsTraffic
Indicates that one entity is capable of handling, carrying, or accommodating the flow or volume of traffic associated with another entity.
-
C.
hasTrafficMode
Indicates the mode or type of traffic associated with or applicable to an entity (e.g., pedestrian, vehicular, public transit).
-
D.
usedForShiftTraffic
Indicates that something is employed to redirect or redistribute traffic flow from one route, area, or channel to another.
-
E.
coversTrafficType
Indicates that one entity includes, handles, or applies to a specified type or category of traffic.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 28, 2026, 8:43 p.m.