Triple
T16194340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Car and Foundry |
E393022
|
entity |
| Predicate | hasSubsidiaryOrPlantType |
P38626
|
FINISHED |
| Object | railcar manufacturing plants |
—
|
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: railcar manufacturing plants | Statement: [American Car and Foundry, hasSubsidiaryOrPlantType, railcar manufacturing plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubsidiaryOrPlantType Context triple: [American Car and Foundry, hasSubsidiaryOrPlantType, railcar manufacturing plants]
-
A.
hasSubsidiaryLabel
Indicates that one entity is identified as a subsidiary or subordinate organization of another entity.
-
B.
hasSubOrganizationType
chosen
Indicates that an organization is associated with or classified under a specific type or category of sub-organization.
-
C.
hasSubsidiaryBusiness
Indicates that one business entity owns or controls another business entity as its subsidiary.
-
D.
usedBySubsidiaryOf
Indicates that something is used by an entity that is a subsidiary of another organization.
-
E.
hasParentCompanyType
Indicates that an entity is associated with a parent company of a specified organizational or business type.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d851188190b2452d165e4fc4bd |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.