Triple
T986387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SGI |
E21289
|
entity |
| Predicate | majorCustomerIndustry |
P13077
|
FINISHED |
| Object | film and visual effects |
—
|
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: film and visual effects | Statement: [SGI, majorCustomerIndustry, film and visual effects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorCustomerIndustry Context triple: [SGI, majorCustomerIndustry, film and visual effects]
-
A.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
B.
majorTradeType
Indicates the primary category or kind of trade activity that characterizes the relationship between the involved entities.
-
C.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
-
D.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
E.
majorTradingCompany
Indicates that the subject is a principal or highly significant company engaged in large-scale trading activities with the object.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b496b7308190a9c201244330b784 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.