Triple
T18125832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de l'Abreuvoir |
E433870
|
entity |
| Predicate | pedestrianFriendliness |
P13973
|
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: [Rue de l'Abreuvoir, pedestrianFriendliness, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestrianFriendliness Context triple: [Rue de l'Abreuvoir, pedestrianFriendliness, high]
-
A.
pedestrianFriendly
chosen
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
B.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
C.
hasPedestrianEnvironment
Indicates that a location or area provides facilities, conditions, or features suitable for pedestrian use and movement.
-
D.
pedestrianizedAreas
Indicates areas where vehicle traffic is restricted or removed so that pedestrians have priority use of the space.
-
E.
pedestrianActivity
Indicates that an entity is engaged in or associated with walking or other on-foot movement or behavior.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddee1efc8190b04324b98de5c9d0 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.