Triple

T7657936
Position Surface form Disambiguated ID Type / Status
Subject Observational selection effects and probability E173432 entity
Predicate mainSubject P3 FINISHED
Object Bayesian epistemology
Bayesian epistemology is a theory of knowledge that models rational belief and updating in terms of subjective probabilities governed by the rules of Bayesian probability theory.
E679748 NE FINISHED

How this triple was built (4 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: Bayesian epistemology | Statement: [Observational selection effects and probability, mainSubject, Bayesian epistemology]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayesian epistemology
Context triple: [Observational selection effects and probability, mainSubject, Bayesian epistemology]
  • A. Epistemic Justification
    Epistemic Justification is a work in philosophy that examines how and when beliefs are rationally supported by evidence and reasoning.
  • B. Truth and Probability
    Truth and Probability is a foundational 1926 essay by philosopher F. P. Ramsey that develops a subjective theory of probability and lays groundwork for modern Bayesian decision theory.
  • C. Logical Foundations of Probability
    Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
  • D. Of Knowledge and Probability
    "Of Knowledge and Probability" is a section in John Locke’s *An Essay Concerning Human Understanding* that analyzes the nature, degrees, and limits of human knowledge in contrast with mere probability or belief.
  • E. Epistemology Naturalized
    Epistemology Naturalized is W.V.O. Quine’s influential proposal to reconceive traditional epistemology as a branch of empirical psychology, focusing on how humans actually form beliefs rather than on a priori justification.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bayesian epistemology
Triple: [Observational selection effects and probability, mainSubject, Bayesian epistemology]
Generated description
Bayesian epistemology is a theory of knowledge that models rational belief and updating in terms of subjective probabilities governed by the rules of Bayesian probability theory.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bayesian epistemology
Target entity description: Bayesian epistemology is a theory of knowledge that models rational belief and updating in terms of subjective probabilities governed by the rules of Bayesian probability theory.
  • A. Epistemic Justification
    Epistemic Justification is a work in philosophy that examines how and when beliefs are rationally supported by evidence and reasoning.
  • B. Truth and Probability
    Truth and Probability is a foundational 1926 essay by philosopher F. P. Ramsey that develops a subjective theory of probability and lays groundwork for modern Bayesian decision theory.
  • C. Logical Foundations of Probability
    Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
  • D. Of Knowledge and Probability
    "Of Knowledge and Probability" is a section in John Locke’s *An Essay Concerning Human Understanding* that analyzes the nature, degrees, and limits of human knowledge in contrast with mere probability or belief.
  • E. Epistemology Naturalized
    Epistemology Naturalized is W.V.O. Quine’s influential proposal to reconceive traditional epistemology as a branch of empirical psychology, focusing on how humans actually form beliefs rather than on a priori justification.
  • F. None of above. chosen

Provenance (5 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7019161548190855a5b1e9f5d7e99 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89b0d345081909a1d4475fa3876f5 completed March 29, 2026, 3:22 a.m.
NEDg Description generation batch_69c89d77b7cc81908120da0121c94537 completed March 29, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69c89ddd81a88190924d41529e94b06b completed March 29, 2026, 3:34 a.m.
Created at: March 27, 2026, 3:59 p.m.