Triple
T21960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Steel Corporation |
E436
|
entity |
| Predicate | hasMajorCustomerSector |
P927
|
FINISHED |
| Object | automotive industry |
—
|
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: automotive industry | Statement: [United States Steel Corporation, hasMajorCustomerSector, automotive industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorCustomerSector Context triple: [United States Steel Corporation, hasMajorCustomerSector, automotive industry]
-
A.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
-
B.
majorCustomer
chosen
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
C.
hasMajorCountry
Indicates that an entity includes, is associated with, or is primarily represented by a particular major country.
-
D.
hasMajorEconomicRegion
Indicates that an entity includes, is associated with, or is part of a primary or significant economic region within a larger economic or geographic context.
-
E.
hasAdvancedTechnologySector
Indicates that an entity possesses or includes a developed sector focused on advanced or high-tech industries, products, or services.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24654724481909ba14b7f68d2a472 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.