Triple
T785423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oxford Road |
E16589
|
entity |
| Predicate | hasPedestrianTrafficLevel |
P19607
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Oxford Road, hasPedestrianTrafficLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianTrafficLevel Context triple: [Oxford Road, hasPedestrianTrafficLevel, high]
-
A.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
B.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
C.
pedestrianFriendly
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
D.
hasPedestrianPlazaOn
Indicates that a pedestrian plaza is located on, or directly associated with, a specified surface, structure, or area.
-
E.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a76b0d6c8190a09b1a0bd4a6eeec |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a67e69288190b3dc278c5bd94155 |
completed | March 1, 2026, 8:50 p.m. |
Created at: March 1, 2026, 7:38 p.m.