Triple
T16533436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intercounty Connector (MD 200) |
E401623
|
entity |
| Predicate | tollCollectionMethod |
P3913
|
FINISHED |
| Object | E-ZPass |
E54620
|
NE 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: E-ZPass | Statement: [Intercounty Connector (MD 200), tollCollectionMethod, E-ZPass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: E-ZPass Context triple: [Intercounty Connector (MD 200), tollCollectionMethod, E-ZPass]
-
A.
E-ZPass
chosen
E-ZPass is an electronic toll collection system widely used on highways and bridges across the eastern United States, allowing drivers to pay tolls automatically without stopping.
-
B.
FasTrak
FasTrak is an electronic toll collection system used on bridges, roads, and express lanes throughout California.
-
C.
SunPass
SunPass is Florida’s statewide electronic toll collection system used on many of the state’s toll roads, bridges, and express lanes.
-
D.
TollTag
TollTag is an electronic toll collection system used on North Texas toll roads, allowing drivers to pay tolls automatically without stopping.
-
E.
Clipper card
The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed97b0881909de106418aca8180 |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006093244081909ae74674de966d6d |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:15 a.m.