Triple

T10023468
Position Surface form Disambiguated ID Type / Status
Subject Bayesian networks E200666 entity
Predicate inferenceAlgorithms P25130 FINISHED
Object variable elimination 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: variable elimination | Statement: [Bayesian networks, inferenceAlgorithms, variable elimination]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: inferenceAlgorithms
Context triple: [Bayesian networks, inferenceAlgorithms, variable elimination]
  • A. supportsInferenceOf
    Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
  • B. relatedAlgorithm chosen
    Indicates that one algorithm has a meaningful connection or association with another algorithm, such as similarity, dependency, or complementary function.
  • C. inceptionApproximation
    Indicates an approximate or estimated starting point or origin of something, rather than an exact inception time.
  • D. predictionAlgorithm
    Indicates a relationship where an algorithm generates predictions or forecasts about outcomes based on input data or observed patterns.
  • E. viewOnInference
    Indicates that one entity forms or expresses a perspective, judgment, or conclusion about another entity as a result of an inferential or reasoning process.
  • 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_69ca831c45f08190ac1505cc15076608 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd7c75548190aa604d90d63dc111 completed April 2, 2026, 1:59 a.m.
PD Predicate disambiguation batch_69cd4b7cd4208190b2253583ee2f892c completed April 1, 2026, 4:44 p.m.
Created at: March 30, 2026, 8:53 p.m.