Triple
T12785287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market Street and Drumm Street |
E305608
|
entity |
| Predicate | hasTransitTrafficLevel |
P106904
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Market Street and Drumm Street, hasTransitTrafficLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransitTrafficLevel Context triple: [Market Street and Drumm Street, hasTransitTrafficLevel, high]
-
A.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
B.
hasCargoTrafficLevel
Indicates the intensity or volume of cargo-related traffic associated with an entity, such as a route, location, or transport facility.
-
C.
hasCommuterTraffic
Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
-
D.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
-
E.
relativeTrafficLevel
Indicates the comparative intensity or volume of traffic between two or more locations, routes, or time periods.
- F. None of above. chosen
Provenance (4 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5cb3c08190b8e1e22de8b96e17 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:29 p.m.