Triple
T37084650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue Neuve |
E918248
|
entity |
| Predicate | hasPedestrianFootfallLevel |
P19607
|
FINISHED |
| Object | very 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: very high | Statement: [Rue Neuve, hasPedestrianFootfallLevel, very high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianFootfallLevel Context triple: [Rue Neuve, hasPedestrianFootfallLevel, very high]
-
A.
hasPedestrianTrafficLevel
chosen
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
B.
hasPedestrianSteps
Indicates that one location or structure is connected to another by pedestrian steps or stairways.
-
C.
hasPedestrianFunction
Indicates that an entity serves a role, purpose, or function specifically related to pedestrians or pedestrian use.
-
D.
hasFootfallPattern
Indicates a characteristic pattern or sequence of steps, movements, or impacts made by an entity’s feet during locomotion or activity.
-
E.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
- 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_69f76e9952b88190a6fe01ba01476520 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe87b609888190913b0c3f787ecdba |
completed | May 9, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69fe8731af48819092084f6f74bf052d |
completed | May 9, 2026, 1 a.m. |
Created at: May 3, 2026, 4:14 p.m.