Triple
T32691197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiseido |
E835859
|
entity |
| Predicate | hasKeyBusinessSegment |
P120776
|
FINISHED |
| Object | Prestige cosmetics |
—
|
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: Prestige cosmetics | Statement: [Shiseido, hasKeyBusinessSegment, Prestige cosmetics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyBusinessSegment Context triple: [Shiseido, hasKeyBusinessSegment, Prestige cosmetics]
-
A.
hasKeyBusinessArea
Indicates that an entity is associated with or operates within a particular primary business area or domain.
-
B.
hasKeyBusiness
Indicates that one entity possesses or is associated with a primary or strategically important business of another entity.
-
C.
hasMarketSegmentFor
chosen
Indicates that an entity targets or serves a specific market segment for its products or services.
-
D.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
E.
hasBusinessSection
Indicates that an entity (such as a publication or website) includes a dedicated section focused on business-related content or topics.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 1, 2026, 1:10 a.m.