Triple
T2613437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsukamoto Station |
E58829
|
entity |
| Predicate | hasStaffedTicketOffice |
P41426
|
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: [Tsukamoto Station, hasStaffedTicketOffice, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffedTicketOffice Context triple: [Tsukamoto Station, hasStaffedTicketOffice, yes]
-
A.
hasBookingOffice
Indicates that one entity maintains or is associated with a booking office where reservations or ticketing services are handled for it.
-
B.
hasSupportingOffice
Indicates that an entity is associated with or served by a particular office that provides support or administrative services to it.
-
C.
hasClerk
Indicates that an entity is served, assisted, or managed by a clerk associated with it.
-
D.
hasCustomerAssistanceArea
Indicates that an entity includes or provides a designated area or facility for assisting customers.
-
E.
fieldOfficePresence
Indicates that an entity maintains a physical field office or on-the-ground operational presence in a particular location or jurisdiction.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd891bcd481909af5340a64ff69f9 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:50 p.m.