Triple
T24726504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMG |
E618167
|
entity |
| Predicate | underlyingCompanyGICSIndustry |
P90899
|
FINISHED |
| Object | Restaurants |
—
|
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: Restaurants | Statement: [CMG, underlyingCompanyGICSIndustry, Restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underlyingCompanyGICSIndustry Context triple: [CMG, underlyingCompanyGICSIndustry, Restaurants]
-
A.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
B.
hasGICSindustry
chosen
Indicates that an entity belongs to, or is classified under, a specific GICS (Global Industry Classification Standard) industry category.
-
C.
underlyingCompany
Indicates that one entity serves as the fundamental or base company upon which another entity (such as a product, instrument, or structure) is built, derived, or dependent.
-
D.
underlyingCompanyType
Indicates the classification or category of company that forms the basis or source for another related entity or instrument.
-
E.
industryOfUnderlyingIssuer
Indicates the industry sector to which the underlying issuer in a financial or contractual arrangement belongs.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:59 a.m.