Triple
T13316593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kintetsu Department Store |
E317202
|
entity |
| Predicate | brandScript |
P74696
|
FINISHED |
| Object | Kanji |
—
|
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: Kanji | Statement: [Kintetsu Department Store, brandScript, Kanji]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandScript Context triple: [Kintetsu Department Store, brandScript, Kanji]
-
A.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
B.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
C.
brandingStyle
chosen
Indicates the specific visual and stylistic approach used to represent a brand’s identity.
-
D.
brandStrategy
Indicates the relationship in which a brand defines and guides how it will be positioned, communicated, and differentiated in the market to achieve its business goals.
-
E.
brandLine
Indicates that one brand is a specific product line or sub-brand offered under another brand.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.