Triple
T24589771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerta de San Vicente |
E608496
|
entity |
| Predicate | hasTrafficAround |
P80729
|
FINISHED |
| Object | glorieta (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: glorieta (roundabout) | Statement: [Puerta de San Vicente, hasTrafficAround, glorieta (roundabout)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficAround Context triple: [Puerta de San Vicente, hasTrafficAround, glorieta (roundabout)]
-
A.
hasHeavyTraffic
Indicates that a location, route, or area is experiencing a high volume of traffic, causing congestion or delays.
-
B.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
C.
hasLevelOfTraffic
Indicates the degree or intensity of traffic present in or affecting a given entity or location.
-
D.
hasCommuterTraffic
Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
-
E.
hasTrafficFeature
chosen
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
- 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9da6eb881909b11d4d4cec8e458 |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.