Triple
T10796721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tri-State Tollway |
E254725
|
entity |
| Predicate | electronicTollCollection |
P395
|
FINISHED |
| Object | I-PASS |
E248378
|
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: I-PASS | Statement: [Tri-State Tollway, electronicTollCollection, I-PASS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I-PASS Context triple: [Tri-State Tollway, electronicTollCollection, I-PASS]
-
A.
I-PASS
chosen
I-PASS is an electronic toll collection system used on Illinois tollways that allows drivers to pay tolls automatically without stopping.
-
B.
iPASS
iPASS is a Taiwanese contactless smart card widely used for public transportation fares and small-value electronic payments.
-
C.
PASPA
PASPA was a 1992 U.S. federal law that effectively banned state-authorized sports betting nationwide until it was struck down by the Supreme Court in 2018.
-
D.
IPSO
IPSO is the independent regulator for the newspaper and magazine industry in the United Kingdom, responsible for enforcing the Editors’ Code of Practice and handling complaints about the press.
-
E.
IPN
IPN is a major Mexican public university system renowned for its strong emphasis on engineering, science, and technology education and research.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73332dbfc8190904434846957b618 |
completed | April 9, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de566352608190ab15e3a4b690c9a5 |
completed | April 14, 2026, 2:59 p.m. |
Created at: April 8, 2026, 9:17 p.m.