Triple
T2121772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTtransit |
E43939
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object |
Go CT Card
Go CT Card is a contactless smart fare card used for paying bus and transit fares across the CTtransit public transportation network in Connecticut.
|
E235922
|
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: Go CT Card | Statement: [CTtransit, fareSystem, Go CT Card]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Go CT Card Context triple: [CTtransit, fareSystem, Go CT Card]
-
A.
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.
-
B.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
C.
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.
-
D.
CTC
CTC is the commonly used abbreviation for the United Nations Security Council’s Counter-Terrorism Committee, which oversees global efforts to combat terrorism.
-
E.
TAP card
The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
- 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: Go CT Card Triple: [CTtransit, fareSystem, Go CT Card]
Generated description
Go CT Card is a contactless smart fare card used for paying bus and transit fares across the CTtransit public transportation network in Connecticut.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Go CT Card Target entity description: Go CT Card is a contactless smart fare card used for paying bus and transit fares across the CTtransit public transportation network in Connecticut.
-
A.
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.
-
B.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
C.
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.
-
D.
CTC
CTC is the commonly used abbreviation for the United Nations Security Council’s Counter-Terrorism Committee, which oversees global efforts to combat terrorism.
-
E.
TAP card
The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb51e8088190a1aeafee4e8dff63 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51999ca08190a726040df6825ba5 |
completed | March 9, 2026, 4:50 a.m. |
| NEDg | Description generation | batch_69ae5209ae40819095e02cafb8112a1f |
completed | March 9, 2026, 4:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae529375788190aead19ec0874f11e |
completed | March 9, 2026, 4:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.