Triple
T10023465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayesian networks |
E200666
|
entity |
| Predicate | structureLearning |
P91764
|
FINISHED |
| Object | score-based methods |
—
|
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: score-based methods | Statement: [Bayesian networks, structureLearning, score-based methods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: structureLearning Context triple: [Bayesian networks, structureLearning, score-based methods]
-
A.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
B.
structureFocus
Indicates that attention or emphasis is placed on the structural aspects or organization of something within the described context.
-
C.
courseStructure
Indicates how a course is organized into its constituent parts, such as modules, units, lessons, and their sequencing or hierarchy.
-
D.
lesson
Indicates that one entity provides or conducts an instructional session or teaching activity for another entity.
-
E.
lessonsLearned
Indicates that certain insights, knowledge, or understanding have been gained from a prior experience, event, or process.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd7c75548190aa604d90d63dc111 |
completed | April 2, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:53 p.m.