Triple
T3272027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denfert-Rochereau |
E68668
|
entity |
| Predicate | hasTrafficSystem |
P17040
|
FINISHED |
| Object | roundabout |
—
|
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: roundabout | Statement: [Denfert-Rochereau, hasTrafficSystem, roundabout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficSystem Context triple: [Denfert-Rochereau, hasTrafficSystem, roundabout]
-
A.
hasTrafficControl
chosen
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
B.
hasTrafficSignals
Indicates that traffic control signals are present at or associated with a given location or roadway feature.
-
C.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
D.
hasTrafficFunction
Indicates that an entity performs, supports, or is assigned a specific function or role related to traffic management or control.
-
E.
hasTrafficIsland
Indicates the presence of a traffic island separating or organizing lanes or directions of vehicular movement within a roadway.
- 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.