Triple
T33649241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rusty |
E862045
|
entity |
| Predicate | locoType |
P122912
|
FINISHED |
| Object | diesel |
—
|
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: diesel | Statement: [Rusty, locoType, diesel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locoType Context triple: [Rusty, locoType, diesel]
-
A.
laterLocomotiveType
Indicates that one locomotive type succeeds or comes after another in time, representing a later development or version in locomotive design.
-
B.
locomotiveTypeContext
chosen
Indicates the contextual relationship specifying the type or classification of a locomotive involved in a given situation or usage.
-
C.
typicalLocomotiveClass
Indicates that one locomotive class is the standard or most commonly used class for a given context, operator, or service.
-
D.
primaryLocomotiveType
Indicates the main method or mechanism by which an entity typically moves or travels.
-
E.
locomotiveTypeHandled
Indicates the type of locomotive that is managed, operated, or otherwise dealt with in a given context or operation.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.