Triple
T20538992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West End station (MARTA) |
E504274
|
entity |
| Predicate | hasCustomerServiceKiosk |
P84695
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [West End station (MARTA), hasCustomerServiceKiosk, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomerServiceKiosk Context triple: [West End station (MARTA), hasCustomerServiceKiosk, yes]
-
A.
hasRetailKiosks
Indicates that one entity operates or maintains retail kiosks associated with or located within another entity.
-
B.
hasCustomerAssistanceArea
Indicates that an entity includes or provides a designated area or facility for assisting customers.
-
C.
hasCustomerServices
chosen
Indicates that an entity provides or is associated with one or more customer service functions or offerings.
-
D.
hasStationManagerKiosk
Indicates that a station manager operates or is assigned to a specific kiosk.
-
E.
hasSelfServiceTicketMachines
Indicates that an entity is equipped with self-service ticket machines available for use.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a290bd8c819091988f511fb5820b |
completed | April 20, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:37 a.m.