Triple

T11002232
Position Surface form Disambiguated ID Type / Status
Subject Gibbs sampling E260029 entity
Predicate basedOn P98 FINISHED
Object Markov chain theory E48274 NE FINISHED

Named-entity recognition

Before disambiguation, gpt-5-mini classified whether the object phrase is a named entity — the step behind the object's NE type shown above.

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: Markov chain theory | Statement: [Gibbs sampling, basedOn, Markov chain theory]

Disambiguation candidates (1 decision)

The exact options the model was shown at each disambiguation step, with the option it chose highlighted — the evidence behind this triple's disambiguated ids.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Markov chain theory
Context triple: [Gibbs sampling, basedOn, Markov chain theory]
  • A. Markov processes chosen
    Markov processes are stochastic processes in which the future evolution depends only on the present state and not on the past history.
  • B. 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.
  • C. Markov
    Markov is a Russian surname most famously associated with mathematician Andrey Markov, known for his pioneering work on stochastic processes and Markov chains.
  • D. 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.
  • E. Markov semigroup
    A Markov semigroup is a family of linear operators describing the time evolution of probability distributions in a Markov process, forming a semigroup under composition and preserving positivity and total mass.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

Stage Batch ID Job type Status
creating batch_69d6aa8a6a548190a750f944ccdc8064 elicitation completed
NER batch_69d796d760008190930228fa77b61b8b ner completed
NED1 batch_69e3453d181081908cb58a957f4d1295 ned_source_triple completed
Created at: April 8, 2026, 9:25 p.m.