Triple
T18222243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | randomForest |
E436333
|
entity |
| Predicate | supportsInputType |
P24486
|
FINISHED |
| Object | data frame |
—
|
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: data frame | Statement: [randomForest, supportsInputType, data frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInputType Context triple: [randomForest, supportsInputType, data frame]
-
A.
hasInputType
Indicates that an entity takes another entity as its input type for its operation, function, or process.
-
B.
supportsKeyboard
Indicates that one entity is compatible with or able to be operated using a keyboard as an input method.
-
C.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
D.
supportsControllerInput
Indicates that an entity is capable of receiving and handling input from a controller device.
-
E.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e47c85108190bd9707b40bdfdb38 |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.