Triple
T187599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RTN |
E4016
|
entity |
| Predicate | underlyingCompanyBusinessFocus |
P6749
|
FINISHED |
| Object | defense systems |
—
|
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: defense systems | Statement: [RTN, underlyingCompanyBusinessFocus, defense systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underlyingCompanyBusinessFocus Context triple: [RTN, underlyingCompanyBusinessFocus, defense systems]
-
A.
company
Indicates that an entity is a business organization engaged in commercial, industrial, or professional activities.
-
B.
majorTradingCompany
Indicates that the subject is a principal or highly significant company engaged in large-scale trading activities with the object.
-
C.
charteredCompany
Indicates that a company has been formally established and granted specific rights or privileges through an official charter, typically by a government or sovereign authority.
-
D.
residentCompany
Indicates that a company is based in, operates from, or has its primary residence in a particular location or jurisdiction.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- F. None of above. chosen
Provenance (4 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594940e48190a3d8efbce46241c3 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a257e763d081908c54ad57d8d3060d |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.