Triple
T978164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osakako Station |
E21103
|
entity |
| Predicate | hasInformationDesk |
P5881
|
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: [Osakako Station, hasInformationDesk, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInformationDesk Context triple: [Osakako Station, hasInformationDesk, yes]
-
A.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
B.
hasInformationService
chosen
Indicates that one entity provides, operates, or is associated with an information-related service for another entity.
-
C.
providesInformationIn
Indicates that one entity supplies or conveys information within or through another entity or context.
-
D.
hasHelpPoint
Indicates that one entity provides or contains a designated help or assistance point for another entity.
-
E.
isServiceCentreFor
Indicates that one entity functions as a service center that provides support, maintenance, or related services for another entity.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b47861808190be56a7bbd926e658 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.