Triple
T626549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (CTA) |
E15830
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | Ventra |
E1909
|
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: Ventra | Statement: [Red Line (CTA), fareSystem, Ventra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ventra Context triple: [Red Line (CTA), fareSystem, Ventra]
-
A.
Ventra
chosen
Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
-
B.
Byfleet
Byfleet is a village and former civil parish in southeast England, situated within the county of Surrey.
-
C.
The Battery
The Battery is a historic defensive seawall and promenade in Charleston, South Carolina, famed for its antebellum homes and views of Charleston Harbor and Fort Sumter.
-
D.
E-ZPass
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.
-
E.
Nissan Leaf
The Nissan Leaf is a mass-market all-electric compact hatchback known for pioneering affordable zero-emission driving.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e587c448190987943a6aad209d1 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56704a2548190879432e2c4246ddf |
completed | March 2, 2026, 10:31 a.m. |
Created at: March 1, 2026, 7:35 p.m.