Triple
T5607269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OTC:NSRGY |
E147263
|
entity |
| Predicate | hasUnderlyingIndustryClassification |
P6744
|
FINISHED |
| Object | Packaged foods and meats |
—
|
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: Packaged foods and meats | Statement: [OTC:NSRGY, hasUnderlyingIndustryClassification, Packaged foods and meats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderlyingIndustryClassification Context triple: [OTC:NSRGY, hasUnderlyingIndustryClassification, Packaged foods and meats]
-
A.
industryOfUnderlyingCompany
chosen
Indicates the industry sector in which the underlying company associated with this entity operates.
-
B.
hasGICSSubIndustry
Indicates that an entity is classified within a specific GICS (Global Industry Classification Standard) sub-industry category.
-
C.
hasUnderlyingLEI
Indicates that an entity is associated with, or identified by, a specific underlying Legal Entity Identifier (LEI).
-
D.
hasUnderlyingCompanyBusinessModel
Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
-
E.
hasParentCompanyIndustry
Indicates that an entity’s parent company operates in, or is associated with, 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020fbb8748190841e5e09db3feef1 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.