Triple
T9500716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AlphaGo Zero |
E229130
|
entity |
| Predicate | trainingStartState |
P88969
|
FINISHED |
| Object | random play |
—
|
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: random play | Statement: [AlphaGo Zero, trainingStartState, random play]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingStartState Context triple: [AlphaGo Zero, trainingStartState, random play]
-
A.
trainingStatus
Indicates the current state or phase of an entity within a training or learning process.
-
B.
trainingOrigin
Indicates the source or context from which an entity’s training, instruction, or preparation was derived.
-
C.
trainingUnder
Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
-
D.
trainingVersion
Indicates that one entity is a specific training iteration, release, or configuration derived from or associated with another entity.
-
E.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983c308c8190bde6858ac1ca8ea5 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca8c6b0f081908334d6c7cf80e03c |
completed | April 1, 2026, 5:10 a.m. |
Created at: March 30, 2026, 7:57 p.m.