Triple
T30375510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaplan turbine |
E772676
|
entity |
| Predicate | hasRunnerType |
P116920
|
FINISHED |
| Object | axial-flow runner |
—
|
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: axial-flow runner | Statement: [Kaplan turbine, hasRunnerType, axial-flow runner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunnerType Context triple: [Kaplan turbine, hasRunnerType, axial-flow runner]
-
A.
hasRunType
Indicates the type or category of a run associated with an entity (e.g., execution mode, run classification, or run configuration).
-
B.
hasRuntimeType
Indicates that an entity is of, or conforms to, a specific type when evaluated at runtime rather than at compile time.
-
C.
runnerType
chosen
Indicates the specific category or style of running associated with an entity (e.g., sprinter, marathoner, trail runner).
-
D.
hasStarterType
Indicates that an entity is associated with a particular starter category or type, typically designating its initial or primary classification.
-
E.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 29, 2026, 7:59 p.m.