Triple

T11961992
Position Surface form Disambiguated ID Type / Status
Subject Brownian filtration E284689 entity
Predicate relatedTo P37 FINISHED
Object strong Markov property of Brownian motion
The strong Markov property of Brownian motion states that, at any stopping time, the future evolution of the process is independent of the past and has the same distribution as a Brownian motion starting from the current position.
E957840 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: strong Markov property of Brownian motion | Statement: [Brownian filtration, relatedTo, strong Markov property of Brownian motion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: strong Markov property of Brownian motion
Context triple: [Brownian filtration, relatedTo, strong Markov property of Brownian motion]
  • A. Brownian filtration
    Brownian filtration is the natural increasing family of σ-algebras generated by a Brownian motion, encoding all information revealed by the process up to each time.
  • B. Dyson Brownian motion
    Dyson Brownian motion is a stochastic process describing the time evolution of eigenvalues of random matrices as if they were interacting particles undergoing Brownian motion, fundamental in random matrix theory.
  • C. Dynkin formula
    Dynkin formula is a fundamental result in the theory of Markov processes that expresses the expected value of a function of the process at a stopping time in terms of its generator and an integral over time.
  • D. Doob’s h-transform
    Doob’s h-transform is a probabilistic technique that conditions Markov processes on future behavior by reweighting paths with a harmonic function, yielding a new process with modified transition dynamics.
  • E. Brownian motion
    Brownian motion is the random, jittery movement of microscopic particles suspended in a fluid, whose explanation provided key evidence for the existence of atoms and the molecular nature of matter.
  • 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: strong Markov property of Brownian motion
Triple: [Brownian filtration, relatedTo, strong Markov property of Brownian motion]
Generated description
The strong Markov property of Brownian motion states that, at any stopping time, the future evolution of the process is independent of the past and has the same distribution as a Brownian motion starting from the current position.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: strong Markov property of Brownian motion
Target entity description: The strong Markov property of Brownian motion states that, at any stopping time, the future evolution of the process is independent of the past and has the same distribution as a Brownian motion starting from the current position.
  • A. Brownian filtration
    Brownian filtration is the natural increasing family of σ-algebras generated by a Brownian motion, encoding all information revealed by the process up to each time.
  • B. Dyson Brownian motion
    Dyson Brownian motion is a stochastic process describing the time evolution of eigenvalues of random matrices as if they were interacting particles undergoing Brownian motion, fundamental in random matrix theory.
  • C. Dynkin formula
    Dynkin formula is a fundamental result in the theory of Markov processes that expresses the expected value of a function of the process at a stopping time in terms of its generator and an integral over time.
  • D. Doob’s h-transform
    Doob’s h-transform is a probabilistic technique that conditions Markov processes on future behavior by reweighting paths with a harmonic function, yielding a new process with modified transition dynamics.
  • E. Brownian motion
    Brownian motion is the random, jittery movement of microscopic particles suspended in a fluid, whose explanation provided key evidence for the existence of atoms and the molecular nature of matter.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037848f481908276716675464464 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471d625c88190baed4ea08853988a completed May 1, 2026, 9:26 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:45 p.m.