Triple
T14168725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itô isometry |
E351146
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Doob martingale inequalities |
E956289
|
NE FINISHED |
How this triple was built (2 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: Doob martingale inequalities | Statement: [Itô isometry, relatedTo, Doob martingale inequalities]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doob martingale inequalities Context triple: [Itô isometry, relatedTo, Doob martingale inequalities]
-
A.
Doob’s maximal inequalities
chosen
Doob’s maximal inequalities are fundamental results in probability theory that provide bounds on the maximum value of a martingale or submartingale in terms of its expected terminal value, playing a key role in convergence and limit theorems.
-
B.
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.
-
C.
Doob–Meyer decomposition
The Doob–Meyer decomposition is a fundamental result in stochastic process theory that uniquely expresses a submartingale as the sum of a martingale and a predictable, increasing process.
-
D.
Khinchin–Kahane type inequalities
Khinchin–Kahane type inequalities are fundamental results in probability and functional analysis that bound moments or norms of random series (often with Rademacher or Gaussian coefficients) in terms of each other, providing powerful tools for studying the geometry of Banach spaces and random processes.
-
E.
Chebyshev inequalities
Chebyshev inequalities are probabilistic bounds that limit how much a random variable’s values can deviate from its mean in terms of its variance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b472288190b4a271daa54aa6cd |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f779248190921c85f99f587296 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 1 a.m.