Triple
T9209088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myeongnyun Station |
E221064
|
entity |
| Predicate | isPassengerOnly |
P86985
|
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: [Myeongnyun Station, isPassengerOnly, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPassengerOnly Context triple: [Myeongnyun Station, isPassengerOnly, yes]
-
A.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
-
B.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
C.
isAllSeater
Indicates that the entity provides only seated accommodation, with no standing room available.
-
D.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
E.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
- F. None of above. chosen
Provenance (4 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b3c8c081909a688ce699928fc0 |
completed | April 1, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6745c17881908df72443e0800068 |
completed | April 1, 2026, 12:31 a.m. |
Created at: March 30, 2026, 7:26 p.m.