Triple
T34575832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Executive Officer of PetMeds |
E887748
|
entity |
| Predicate | employerBrandName |
P77429
|
FINISHED |
| Object | PetMeds |
—
|
NE NERFINISHED |
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: PetMeds | Statement: [Chief Executive Officer of PetMeds, employerBrandName, PetMeds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerBrandName Context triple: [Chief Executive Officer of PetMeds, employerBrandName, PetMeds]
-
A.
employerBrandingFor
Indicates that one entity develops, manages, or represents the employer brand or employer reputation on behalf of another entity.
-
B.
typicalEmployerBrand
chosen
Indicates that an entity is the employer brand that is most commonly or characteristically associated with another entity.
-
C.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
D.
employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
-
E.
companyFullName
Indicates that the relationship specifies the complete, official legal name of a company.
- 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_69f349d1a5fc81908557a46875b2f157 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 1, 2026, 2:03 a.m.