Triple
T930079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterCity |
E20070
|
entity |
| Predicate | typicalOperatorType |
P21524
|
FINISHED |
| Object | national railway 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: national railway company | Statement: [InterCity, typicalOperatorType, national railway company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOperatorType Context triple: [InterCity, typicalOperatorType, national railway company]
-
A.
typeOfOperation
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
B.
otherOperator
Indicates a relationship where one operator is distinguished from, or serves as an alternative to, another operator within the same context or system.
-
C.
operator
Indicates that one entity functions as the operator (controller or handler) of another entity, such as a system, device, or process.
-
D.
operationOf
Indicates that one entity is the function, activity, or process carried out by another entity (such as a system, device, or organization).
-
E.
operationType
Indicates the specific kind of operation or action being performed or recorded in the relationship between entities.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b29876348190a29f4ff9878074a5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b2f4e3fc81908c8a2d1fbef9c5d2 |
completed | March 1, 2026, 9:43 p.m. |
Created at: March 1, 2026, 7:40 p.m.