Triple
T3272025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denfert-Rochereau |
E68668
|
entity |
| Predicate | hasNearbyRailwayInfrastructure |
P231
|
FINISHED |
| Object | RER B tunnel |
—
|
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: RER B tunnel | Statement: [Denfert-Rochereau, hasNearbyRailwayInfrastructure, RER B tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRailwayInfrastructure Context triple: [Denfert-Rochereau, hasNearbyRailwayInfrastructure, RER B tunnel]
-
A.
hasNearbyRailway
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
B.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
E.
adjacentToInfrastructure
chosen
Indicates that one entity is located directly next to or in immediate proximity to a piece of 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff6308881908886a44804a0bb09 |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.