Triple

T17181978
Position Surface form Disambiguated ID Type / Status
Subject Sheldon M. Ross E417005 entity
Predicate notableWork P4 FINISHED
Object Stochastic Processes
Stochastic Processes is a widely used textbook that introduces the theory and applications of random processes in fields such as probability, statistics, engineering, and operations research.
E274130 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: Stochastic Processes | Statement: [Sheldon M. Ross, notableWork, Stochastic Processes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stochastic Processes
Context triple: [Sheldon M. Ross, notableWork, Stochastic Processes]
  • A. Stochastic Processes
    "Stochastic Processes" is a foundational textbook by Emanuel Parzen that rigorously introduces the theory and applications of random processes in probability and statistics.
  • B. Stochastic Processes
    Stochastic Processes is a foundational 1953 monograph by Joseph L. Doob that rigorously develops the theory of stochastic processes and modern probability using measure-theoretic methods.
  • C. Markov processes
    Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
  • D. Lévy processes
    Lévy processes are a class of stochastic processes with stationary, independent increments that generalize random walks and Brownian motion, widely used to model jump-like and continuous-time random phenomena in probability theory and finance.
  • E. "Continuous Markov Processes and Stochastic Equations"
    "Continuous Markov Processes and Stochastic Equations" is a foundational mathematical work that rigorously develops the theory of continuous-time Markov processes and their representation via stochastic differential equations.
  • 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: Stochastic Processes
Triple: [Sheldon M. Ross, notableWork, Stochastic Processes]
Generated description
Stochastic Processes is a widely used textbook that introduces the theory and applications of random processes in fields such as probability, statistics, engineering, and operations research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stochastic Processes
Target entity description: Stochastic Processes is a widely used textbook that introduces the theory and applications of random processes in fields such as probability, statistics, engineering, and operations research.
  • A. Stochastic Processes chosen
    "Stochastic Processes" is a foundational textbook by Emanuel Parzen that rigorously introduces the theory and applications of random processes in probability and statistics.
  • B. Stochastic Processes
    Stochastic Processes is a foundational 1953 monograph by Joseph L. Doob that rigorously develops the theory of stochastic processes and modern probability using measure-theoretic methods.
  • C. Markov processes
    Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
  • D. Lévy processes
    Lévy processes are a class of stochastic processes with stationary, independent increments that generalize random walks and Brownian motion, widely used to model jump-like and continuous-time random phenomena in probability theory and finance.
  • E. "Continuous Markov Processes and Stochastic Equations"
    "Continuous Markov Processes and Stochastic Equations" is a foundational mathematical work that rigorously develops the theory of continuous-time Markov processes and their representation via stochastic differential equations.
  • F. None of above.

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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42d934ec08190acc47073758ac3c0 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a014847a19481909b1249c2fe428bfc completed May 11, 2026, 3:08 a.m.
NEDg Description generation batch_6a014cf269b48190bf58eb71a9fec897 completed May 11, 2026, 3:28 a.m.
NED2 Entity disambiguation (via description) batch_6a014d5d10b4819086969145c2d4fb56 completed May 11, 2026, 3:30 a.m.
Created at: April 10, 2026, 5:37 a.m.