Triple

T1819307
Position Surface form Disambiguated ID Type / Status
Subject Alfréd Rényi E40505 entity
Predicate notableWork P4 FINISHED
Object Probability Theory
Probability Theory is a foundational branch of mathematics that studies random phenomena and quantifies uncertainty using concepts such as probability measures, random variables, and distributions.
E204642 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: Probability Theory | Statement: [Alfréd Rényi, notableWork, Probability Theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Probability Theory
Context triple: [Alfréd Rényi, notableWork, Probability Theory]
  • A. Probability and Related Topics in Physical Sciences
    "Probability and Related Topics in Physical Sciences" is a classic book by mathematician Mark Kac that introduces and applies probabilistic methods to problems in physics and related scientific fields.
  • B. Wahrscheinlichkeitslehre
    Wahrscheinlichkeitslehre is a foundational work in the philosophy and axiomatization of probability theory by Hans Reichenbach, influential in both mathematics and logical empiricism.
  • 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. A Treatise on Probability
    A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
  • E. Bayesian inference
    Bayesian inference is a statistical framework that updates the probability of hypotheses as more evidence or data becomes available, using Bayes’ theorem to combine prior beliefs with observed information.
  • 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: Probability Theory
Triple: [Alfréd Rényi, notableWork, Probability Theory]
Generated description
Probability Theory is a foundational branch of mathematics that studies random phenomena and quantifies uncertainty using concepts such as probability measures, random variables, and distributions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Probability Theory
Target entity description: Probability Theory is a foundational branch of mathematics that studies random phenomena and quantifies uncertainty using concepts such as probability measures, random variables, and distributions.
  • A. Probability and Related Topics in Physical Sciences
    "Probability and Related Topics in Physical Sciences" is a classic book by mathematician Mark Kac that introduces and applies probabilistic methods to problems in physics and related scientific fields.
  • B. Wahrscheinlichkeitslehre
    Wahrscheinlichkeitslehre is a foundational work in the philosophy and axiomatization of probability theory by Hans Reichenbach, influential in both mathematics and logical empiricism.
  • 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. A Treatise on Probability
    A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
  • E. Bayesian inference
    Bayesian inference is a statistical framework that updates the probability of hypotheses as more evidence or data becomes available, using Bayes’ theorem to combine prior beliefs with observed information.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65f9f32c819084948e7ce7fa6f2e completed March 6, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf629af48190a27fddc764e306a7 completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc07e9ebc819082566cc98025b4ae completed March 8, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69adc1304a808190a999e71dfa39162a completed March 8, 2026, 6:34 p.m.
Created at: March 4, 2026, 7:32 p.m.