Triple
T10849144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EZ TAG |
E256093
|
entity |
| Predicate | tollRoadType |
P73181
|
FINISHED |
| Object | electronic toll road |
—
|
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: electronic toll road | Statement: [EZ TAG, tollRoadType, electronic toll road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tollRoadType Context triple: [EZ TAG, tollRoadType, electronic toll road]
-
A.
tollingType
Indicates the specific method or basis by which a toll, fee, or charge is applied or calculated in a given context.
-
B.
typeOfTollSystem
chosen
Indicates the specific kind or category of toll collection system used in a given context.
-
C.
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.
-
D.
hasTollBoothsAt
Indicates that toll booths are present at or associated with a particular location or segment of infrastructure.
-
E.
tollFacilityName
Indicates the name assigned to a toll facility where tolls are collected.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75115e4a88190b77be46b63db0c84 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.