Triple
T17561646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XGBoost |
E427706
|
entity |
| Predicate | supportsLearningTask |
P94878
|
FINISHED |
| Object | supervised learning |
—
|
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: supervised learning | Statement: [XGBoost, supportsLearningTask, supervised learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLearningTask Context triple: [XGBoost, supportsLearningTask, supervised learning]
-
A.
supportsLearningMechanism
Indicates that one entity facilitates, enables, or enhances the learning mechanism or process of another entity.
-
B.
supportsInstruction
Indicates that one entity provides assistance, resources, or functionality that enables or facilitates the instruction or teaching activities of another entity.
-
C.
teachingSupportedBy
Indicates that a teaching activity is enabled, facilitated, or enhanced by support from another entity (such as resources, tools, services, or personnel).
-
D.
supportsSTEMLearning
Indicates that one entity provides resources, opportunities, or conditions that facilitate or enhance another entity’s learning in science, technology, engineering, and mathematics (STEM).
-
E.
usesLearningMechanism
chosen
Indicates that one entity employs or applies a particular learning mechanism or method in its functioning or behavior.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456274c888190ac80402e391674dd |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.