Triple
T30338021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leela Chess Zero |
E771672
|
entity |
| Predicate | hasTrainingDataSource |
P196823
|
FINISHED |
| Object | self-play games generated by engine |
—
|
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: self-play games generated by engine | Statement: [Leela Chess Zero, hasTrainingDataSource, self-play games generated by engine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingDataSource Context triple: [Leela Chess Zero, hasTrainingDataSource, self-play games generated by engine]
-
A.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
B.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
C.
hasTrainingImages
Indicates that an entity is associated with one or more images used to train a model or learning system.
-
D.
hasTrainingPipelineFrom
Indicates that something is produced or derived as the result of a specified training pipeline or process.
-
E.
hasTrainingFunction
Indicates that one entity serves as a training function or mechanism for another 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
| PDg | Predicate description generation | batch_69fe6b7a823881909dc2037fe25bea24 |
completed | May 8, 2026, 11:02 p.m. |
Created at: April 29, 2026, 7:54 p.m.