Triple
T3832291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMC |
E91040
|
entity |
| Predicate | hasGICSIndustry |
P13077
|
FINISHED |
| Object | Automobiles |
—
|
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: Automobiles | Statement: [HMC, hasGICSIndustry, Automobiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGICSIndustry Context triple: [HMC, hasGICSIndustry, Automobiles]
-
A.
hasGICSSubIndustry
Indicates that an entity is classified within a specific GICS (Global Industry Classification Standard) sub-industry category.
-
B.
hasParentCompanyIndustry
Indicates that an entity’s parent company operates in, or is associated with, a specified industry.
-
C.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
D.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
-
E.
SICCode
Indicates the standardized industrial classification code that categorizes the primary type of economic activity associated with an entity or relationship.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.