Triple
T2653901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenmore station |
E53962
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | CharlieCard |
E3327
|
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: CharlieCard | Statement: [Kenmore station, fareSystem, CharlieCard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CharlieCard Context triple: [Kenmore station, fareSystem, CharlieCard]
-
A.
CharlieCard
chosen
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
B.
CharmCard
CharmCard is a contactless smart fare card used for paying transit fares across the Maryland Transit Administration’s bus, rail, and other public transportation services.
-
C.
Card
Card is a surname most notably borne by Andrew Card, a former White House Chief of Staff under U.S. President George W. Bush.
-
D.
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.
-
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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd932a35881909568839589f12062 |
completed | March 7, 2026, 7:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98d0dbd08190a317dfe1844840c5 |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:53 p.m.