Triple
T31460193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voie Georges-Pompidou |
E802566
|
entity |
| Predicate | hasCarFreeEvents |
P91338
|
FINISHED |
| Object | Paris Plages |
—
|
NE NERFINISHED |
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: Paris Plages | Statement: [Voie Georges-Pompidou, hasCarFreeEvents, Paris Plages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarFreeEvents Context triple: [Voie Georges-Pompidou, hasCarFreeEvents, Paris Plages]
-
A.
hasPublicEventsIn
Indicates that an entity organizes or holds public events within a specified location or context.
-
B.
hasTransportationEvent
Indicates that an entity is involved in or associated with a specific transportation-related occurrence, such as a trip, transfer, or movement event.
-
C.
hasRecreationEvent
Indicates that an entity is associated with, organizes, or participates in a recreational event or activity.
-
D.
hasOfficialEvents
Indicates that an entity organizes, hosts, or is associated with formally recognized or sanctioned events.
-
E.
hasOccasionalEvent
chosen
Indicates that an event or activity occurs irregularly or infrequently in relation to a given entity or context.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 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: April 30, 2026, 9:19 p.m.