Triple
T13950174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka urban rail network |
E335499
|
entity |
| Predicate | fareSystemFeature |
P112377
|
FINISHED |
| Object | IC card compatibility |
—
|
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: IC card compatibility | Statement: [Osaka urban rail network, fareSystemFeature, IC card compatibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareSystemFeature Context triple: [Osaka urban rail network, fareSystemFeature, IC card compatibility]
-
A.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
B.
fareSystemUse
Indicates the use or application of a particular fare system for travel, ticketing, or pricing.
-
C.
fareContext
Indicates the pricing or fare-related conditions under which a transaction, service, or travel arrangement is applied.
-
D.
fareTypes
Indicates the categories or kinds of fares (e.g., ticket or pricing options) that apply to a given travel or service offering.
-
E.
hasFareZoneFeature
Indicates that an entity is associated with a specific fare zone or fare-related area designation.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e131c608190b4ffdbada24a3208 |
completed | April 14, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:17 p.m.