Triple
T30505355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeast Extension |
E776253
|
entity |
| Predicate | usesTollCollection |
P3913
|
FINISHED |
| Object | electronic toll collection |
—
|
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 collection | Statement: [Northeast Extension, usesTollCollection, electronic toll collection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTollCollection Context triple: [Northeast Extension, usesTollCollection, electronic toll collection]
-
A.
appliesTollTo
Indicates that a fee or charge is imposed on a subject for using, accessing, or passing through something.
-
B.
hasToll
Indicates that the use, access, or passage associated with something requires payment of a toll or fee.
-
C.
operatesTollSystem
Indicates that an entity is responsible for running and managing a toll collection system.
-
D.
hasTollAgency
Indicates that a transportation facility or route is operated, managed, or overseen by a specific toll-collecting agency.
-
E.
tollingType
chosen
Indicates the specific method or basis by which a toll, fee, or charge is applied or calculated in a given context.
- 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_69f2249a155c8190b1d512106007e9bb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 29, 2026, 8:15 p.m.