Triple
T375009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Standard Railroad of the World |
E8351
|
entity |
| Predicate | associatedWithCompanyType |
P3580
|
FINISHED |
| Object | railroad company |
—
|
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: railroad company | Statement: [The Standard Railroad of the World, associatedWithCompanyType, railroad company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCompanyType Context triple: [The Standard Railroad of the World, associatedWithCompanyType, railroad company]
-
A.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
-
B.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
C.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
D.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
E.
organizationType
chosen
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec1585648190943f1c698e9b2d81 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.