Triple
T16249695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boltzmann–Kac equation |
E394467
|
entity |
| Predicate | usesConcept |
P531
|
FINISHED |
| Object | Markov process |
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 process | Statement: [Boltzmann–Kac equation, usesConcept, Markov process]
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 process Context triple: [Boltzmann–Kac equation, usesConcept, Markov process]
-
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.
Markov
Markov is a Russian surname most famously associated with mathematician Andrey Markov, known for his pioneering work on stochastic processes and Markov chains.
-
C.
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.
-
D.
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.
-
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_69d87f2171208190951025e526947816 |
elicitation | completed |
| NER | batch_69e2459606f88190a53905186f7f73be |
ner | completed |
| NED1 | batch_6a000ee568a48190835ce76f84461044 |
ned_source_triple | completed |
Created at: April 10, 2026, 5:04 a.m.