Triple
T9500684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AlphaGo Zero |
E229130
|
entity |
| Predicate | usesTrainingData |
P20525
|
FINISHED |
| Object | no human game data |
—
|
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: no human game data | Statement: [AlphaGo Zero, usesTrainingData, no human game data]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainingData Context triple: [AlphaGo Zero, usesTrainingData, no human game data]
-
A.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
B.
trainingDataIncludes
Indicates that one entity’s training dataset contains or incorporates the other entity as part of its data.
-
C.
trainingUse
chosen
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
D.
trainingDataType
Indicates the type or category of data used for training a model, system, or process.
-
E.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
- 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_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. |
Created at: March 30, 2026, 7:57 p.m.