Triple
T12451728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNA |
E297547
|
entity |
| Predicate | companyNotableBrandCategory |
P39625
|
FINISHED |
| Object | home care |
—
|
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: home care | Statement: [UNA, companyNotableBrandCategory, home care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: companyNotableBrandCategory Context triple: [UNA, companyNotableBrandCategory, home care]
-
A.
associatedBrandCategory
chosen
Indicates that a brand is linked to or classified under a particular product or service category.
-
B.
notableBrandElement
Indicates that one entity is a significant or distinguishing brand-related feature, component, or asset of another entity.
-
C.
notableManufacturer
Indicates that an entity is a well-known or prominent producer or maker of another entity.
-
D.
notableBusinessType
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
-
E.
hasBrandRecognitionFor
Indicates that one entity is aware of, recognizes, or can identify the brand of 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.