Triple
T32188417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Honest Company |
E822167
|
entity |
| Predicate | brandNameRefersTo |
P174979
|
FINISHED |
| Object | honesty in ingredients and labeling |
—
|
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: honesty in ingredients and labeling | Statement: [The Honest Company, brandNameRefersTo, honesty in ingredients and labeling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandNameRefersTo Context triple: [The Honest Company, brandNameRefersTo, honesty in ingredients and labeling]
-
A.
brandNameType
Indicates the specific type or category associated with a brand name within a broader branding or naming system.
-
B.
referencesBrand
Indicates that one entity mentions, cites, or otherwise refers to a specific brand in its content or context.
-
C.
brandNameUsedIn
Indicates that a particular brand name is used or appears within a specified context, such as a product, document, or communication.
-
D.
brandNumber
Indicates the identifying number or code assigned to a particular brand within a system or dataset.
-
E.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
- F. None of above. chosen
Provenance (4 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6cd9bae8c8190b528641499162a75 |
completed | May 3, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cd119cac8190a0b3ebe8b9c742c2 |
completed | May 3, 2026, 4:20 a.m. |
Created at: May 1, 2026, 12:35 a.m.