Triple
T13032438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champion |
E326473
|
entity |
| Predicate | trainCategory |
P107548
|
FINISHED |
| Object | named streamliner |
—
|
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: named streamliner | Statement: [Champion, trainCategory, named streamliner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainCategory Context triple: [Champion, trainCategory, named streamliner]
-
A.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
B.
busCategory
Indicates the classification or type of a bus within a defined categorization system.
-
C.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
D.
trainsetType
Indicates the specific category or role of a dataset within a training process (e.g., training, validation, or test set).
-
E.
railwayClass
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efe72348190b52fb4068f5fb829 |
completed | April 10, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e3df2288190a7f27d31d248bb7f |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 8:54 p.m.