Triple
T1923067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AlphaZero |
E40166
|
entity |
| Predicate | learningObjective |
P12747
|
FINISHED |
| Object | maximize expected game outcome |
—
|
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: maximize expected game outcome | Statement: [AlphaZero, learningObjective, maximize expected game outcome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learningObjective Context triple: [AlphaZero, learningObjective, maximize expected game outcome]
-
A.
educationalObjective
Indicates the intended learning goal, skill, or competency that an educational resource, activity, or program is designed to achieve.
-
B.
trainingObjective
chosen
Indicates the goal or target outcome that a training process is designed to achieve.
-
C.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
D.
controlObjective
Indicates that one entity defines or specifies a control goal or target that another entity is intended to achieve or satisfy.
-
E.
strategicGoal
Indicates that one entity represents a long-term objective or desired outcome that another entity is intentionally aiming to achieve or align actions toward.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb23459ac819088ded5bfac9d4aad |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.