Triple
T4931989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ridgeland station |
E110716
|
entity |
| Predicate | hasFarecardType |
P5430
|
FINISHED |
| Object | contactless smart card |
—
|
LITERAL 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: contactless smart card | Statement: [Ridgeland station, hasFarecardType, contactless smart card]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFarecardType Context triple: [Ridgeland station, hasFarecardType, contactless smart card]
-
A.
cardType
chosen
Indicates the classification or category assigned to a card within a given system or context.
-
B.
hasBankType
Indicates that an entity is associated with or classified by a particular type or category of bank.
-
C.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
D.
hasFareZoneCode
Indicates that an entity is associated with a specific fare zone identifier used for pricing or tariff purposes.
-
E.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
- F. None of above.
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_69bd4415190c8190817bee7ec9f9f944 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7063c57c8190a5a6fb3586238d35 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.