Triple
T20600288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyu Setagaya Line |
E506158
|
entity |
| Predicate | hasFareCardBrand |
P69490
|
FINISHED |
| Object | Tokyu Card compatible IC cards |
—
|
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: Tokyu Card compatible IC cards | Statement: [Tokyu Setagaya Line, hasFareCardBrand, Tokyu Card compatible IC cards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFareCardBrand Context triple: [Tokyu Setagaya Line, hasFareCardBrand, Tokyu Card compatible IC cards]
-
A.
hasFareCardVendor
Indicates that an entity provides or is associated with a machine or service point where fare cards can be purchased, reloaded, or otherwise obtained.
-
B.
cardBrandsInvolved
Indicates that specific payment card brands are involved or participate in a given transaction, process, or context.
-
C.
hadCoBrandedCreditCardsWith
Indicates that two entities jointly issued or partnered on one or more co-branded credit card products.
-
D.
compatibleICCardBrand
chosen
Indicates that one entity (such as a device or system) supports and can properly operate with IC cards of the specified brand.
-
E.
cardBackBrand
Indicates the brand associated with the back side of a card.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1ef9ac8190b05e23c149529cb9 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.