Triple
T7547283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marylebone Road |
E178437
|
entity |
| Predicate | hasCongestionChargeBoundary |
P77924
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Marylebone Road, hasCongestionChargeBoundary, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCongestionChargeBoundary Context triple: [Marylebone Road, hasCongestionChargeBoundary, yes]
-
A.
hasTollSegment
Indicates that a route, road, or path includes a segment where a toll must be paid.
-
B.
hasTollBoothsAt
Indicates that toll booths are present at or associated with a particular location or segment of infrastructure.
-
C.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
-
D.
hasToll
Indicates that the use, access, or passage associated with something requires payment of a toll or fee.
-
E.
isTollFacilityOf
Indicates that a facility (such as a toll booth, plaza, or gantry) is part of, or used to collect tolls for, a specific toll road or toll transportation infrastructure.
- 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_69c69f2cbe08819088f9eb0c03ef529b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f89a7b2c8190b2ca57edbb4f0390 |
completed | March 27, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:49 p.m.