Triple
T7087457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renee Lawson Hardy |
E165111
|
entity |
| Predicate | coFoundedInIndustry |
P40664
|
FINISHED |
| Object | natural foods grocery |
—
|
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: natural foods grocery | Statement: [Renee Lawson Hardy, coFoundedInIndustry, natural foods grocery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coFoundedInIndustry Context triple: [Renee Lawson Hardy, coFoundedInIndustry, natural foods grocery]
-
A.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
-
B.
hasFoundingIndustryAssociation
Indicates that an entity is associated with an industry organization that played a role in its founding or establishment.
-
C.
associatedCompanyFoundedIn
Indicates that the related company was founded in the specified year or time period.
-
D.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
E.
emergedInIndustry
chosen
Indicates that an entity first appeared, originated, or came into prominence within a specified industry.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e513d9b08190a8a8d213c2264ce4 |
completed | March 27, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c172148190bf290c07bf579d1f |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:41 p.m.