Triple
T4293658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3C |
E99656
|
entity |
| Predicate | hasLearningType |
P24513
|
FINISHED |
| Object | policy gradient method |
—
|
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: policy gradient method | Statement: [A3C, hasLearningType, policy gradient method]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningType Context triple: [A3C, hasLearningType, policy gradient method]
-
A.
hasTrainingType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
B.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
C.
hasModeOfStudy
Indicates the method or format by which an entity (typically a learner) undertakes their studies, such as full-time, part-time, online, or in-person.
-
D.
hasEducationalProfile
Indicates that an entity is associated with a specific educational profile, detailing its education-related characteristics, qualifications, or academic background.
-
E.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with another entity.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35082228081908504e3fd7c4ca1e8 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.