Triple
T2941089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrorail |
E79386
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object |
EASY Card
The EASY Card is a contactless smart card used as a stored-value payment method for public transit services in the Miami-Dade area.
|
E311296
|
NE FINISHED |
How this triple was built (4 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: EASY Card | Statement: [Metrorail, fareSystem, EASY Card]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EASY Card Context triple: [Metrorail, fareSystem, EASY Card]
-
A.
Breeze Card
The Breeze Card is a reusable smart fare card used for paying transit fares across the Metropolitan Atlanta Rapid Transit Authority (MARTA) system in Atlanta, Georgia.
-
B.
Presto card
The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
-
C.
Go-To Card
The Go-To Card is a reusable, contactless smart card used to pay fares on the Minneapolis–Saint Paul METRO transit system.
-
D.
OPUS card
The OPUS card is a reusable, contactless smart card used for public transit fare payment across the greater Montreal area and other regions in Quebec.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: EASY Card Triple: [Metrorail, fareSystem, EASY Card]
Generated description
The EASY Card is a contactless smart card used as a stored-value payment method for public transit services in the Miami-Dade area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: EASY Card Target entity description: The EASY Card is a contactless smart card used as a stored-value payment method for public transit services in the Miami-Dade area.
-
A.
Breeze Card
The Breeze Card is a reusable smart fare card used for paying transit fares across the Metropolitan Atlanta Rapid Transit Authority (MARTA) system in Atlanta, Georgia.
-
B.
Presto card
The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
-
C.
Go-To Card
The Go-To Card is a reusable, contactless smart card used to pay fares on the Minneapolis–Saint Paul METRO transit system.
-
D.
OPUS card
The OPUS card is a reusable, contactless smart card used for public transit fare payment across the greater Montreal area and other regions in Quebec.
-
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. chosen
Provenance (5 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad986f38948190a636a826693a9d4f |
completed | March 8, 2026, 3:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08686b0388190a214ad8a615f2da5 |
completed | March 10, 2026, 9 p.m. |
| NEDg | Description generation | batch_69b0d312b82c81908abbb005560b89a0 |
completed | March 11, 2026, 2:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0d392b8cc8190804a1bf06785d7d0 |
completed | March 11, 2026, 2:29 a.m. |
Created at: March 8, 2026, 2:56 p.m.