Triple
T30337993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leela Chess Zero |
E771672
|
entity |
| Predicate | usesEvaluation |
P77543
|
FINISHED |
| Object | deep neural network |
—
|
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: deep neural network | Statement: [Leela Chess Zero, usesEvaluation, deep neural network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEvaluation Context triple: [Leela Chess Zero, usesEvaluation, deep neural network]
-
A.
evaluationUse
chosen
Indicates that something is used as a basis, tool, or resource for evaluating or assessing something else.
-
B.
supportsEvaluation
Indicates that one entity provides the necessary functionality, resources, or conditions for another entity to be assessed, tested, or evaluated.
-
C.
isEvaluative
Indicates that one entity expresses a judgment, assessment, or value-based evaluation about another entity or situation.
-
D.
usesExpression
Indicates that one entity employs or applies a particular expression (such as a phrase, symbol, or formula) in its communication or representation.
-
E.
hasEvaluationType
Indicates that an entity is associated with a specific kind or category of evaluation applied to it.
- 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 7:54 p.m.