Triple
T21395335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue du Vieux-Marché-aux-Poissons |
E527763
|
entity |
| Predicate | hasPedestrianExperience |
P83965
|
FINISHED |
| Object | historic ambiance |
—
|
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: historic ambiance | Statement: [Rue du Vieux-Marché-aux-Poissons, hasPedestrianExperience, historic ambiance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPedestrianExperience Context triple: [Rue du Vieux-Marché-aux-Poissons, hasPedestrianExperience, historic ambiance]
-
A.
hasPedestrianSteps
Indicates that one location or structure is connected to another by pedestrian steps or stairways.
-
B.
hasPedestrianFunction
Indicates that an entity serves a role, purpose, or function specifically related to pedestrians or pedestrian use.
-
C.
hasRideExperience
Indicates that one entity has undergone, participated in, or possesses experience with a particular ride or riding activity in relation to another entity.
-
D.
hasPedestrianEnvironment
chosen
Indicates that a location or area provides facilities, conditions, or features suitable for pedestrian use and movement.
-
E.
hasTrailExperience
Indicates that an entity has prior experience or familiarity with using or navigating trails.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62cd30f08190aba90afed6116a2a |
completed | April 26, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69e61633f8208190a2a849457c4e4198 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:13 p.m.