Triple
T9440049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porte de Vincennes |
E227619
|
entity |
| Predicate | hasMetroAccess |
P56786
|
FINISHED |
| Object | underground platforms |
—
|
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: underground platforms | Statement: [Porte de Vincennes, hasMetroAccess, underground platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetroAccess Context triple: [Porte de Vincennes, hasMetroAccess, underground platforms]
-
A.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
-
B.
hasTransitAccessTo
Indicates that one place or entity is reachable from another via public or shared transportation services.
-
C.
hasSubway
chosen
Indicates that a place is served by or contains a subway (metro) system.
-
D.
hasMetropolitanConnectionWith
Indicates that there is a significant relationship or linkage between two entities based on shared or interacting metropolitan areas, such as through infrastructure, services, or regional integration.
-
E.
hasUrbanAccess
Indicates that an entity has access to urban areas, services, or infrastructure.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee36f908190826994db91b18466 |
completed | April 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.