Triple
T6372992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Corporation |
E143394
|
entity |
| Predicate | hasMajorCustomerType |
P809
|
FINISHED |
| Object | industrial companies |
—
|
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: industrial companies | Statement: [Union Pacific Corporation, hasMajorCustomerType, industrial companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorCustomerType Context triple: [Union Pacific Corporation, hasMajorCustomerType, industrial companies]
-
A.
hasMajorTenantType
Indicates that an entity (such as a property or building) is associated with a primary or predominant type of tenant.
-
B.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
C.
hasCustomers
Indicates that an entity maintains a business relationship in which other entities purchase or receive its goods or services as customers.
-
D.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
E.
customerType
chosen
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06829d76c819092b476631459233a |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.