Triple
T30338003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leela Chess Zero |
E771672
|
entity |
| Predicate | isTrainedBy |
P171583
|
FINISHED |
| Object | distributed volunteer computing |
—
|
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: distributed volunteer computing | Statement: [Leela Chess Zero, isTrainedBy, distributed volunteer computing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTrainedBy Context triple: [Leela Chess Zero, isTrainedBy, distributed volunteer computing]
-
A.
trainedAs
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
B.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
C.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
-
D.
commonlyTrainedWith
Indicates that two entities are typically trained, practiced, or learned together as part of the same routine, curriculum, or skill set.
-
E.
hasTrainedAt
Indicates that an entity has received training, education, or instruction at a specified place or institution.
- 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_69f6a1ac56b88190a820434b65c9fa23 |
completed | May 3, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 29, 2026, 7:54 p.m.