Triple
T17612704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AGC |
E429000
|
entity |
| Predicate | usedInRailwayTickets |
P128284
|
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: [AGC, usedInRailwayTickets, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInRailwayTickets Context triple: [AGC, usedInRailwayTickets, yes]
-
A.
usedInE-tickets
Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
-
B.
usedOnRailCards
Indicates that something (such as a discount, feature, or rule) is applied to or valid for rail cards.
-
C.
usedForTicketType
Indicates that something is utilized or applicable for a specific type or category of ticket.
-
D.
usedBetweenStations
Indicates that something (such as a service, route, or resource) is utilized in the context of travel or operation between two stations.
-
E.
usedForRailwayTimetables
Indicates that something is employed in the creation, organization, or presentation of railway timetables.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2eaa348190a8226eef8c0d6e31 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:51 a.m.