Triple
T11961511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert C. Merton |
E284678
|
entity |
| Predicate | notableIdea |
P4
|
FINISHED |
| Object |
Merton’s portfolio problem
Merton’s portfolio problem is a foundational continuous-time optimization model in financial economics that determines an investor’s optimal consumption and investment strategy under uncertainty.
|
E956282
|
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: Merton’s portfolio problem | Statement: [Robert C. Merton, notableIdea, Merton’s portfolio problem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merton’s portfolio problem Context triple: [Robert C. Merton, notableIdea, Merton’s portfolio problem]
-
A.
Foundations of a General Theory of Sequential Decision Functions
Foundations of a General Theory of Sequential Decision Functions is a seminal work in statistics that established the mathematical foundations of sequential analysis and optimal decision-making under uncertainty.
-
B.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
-
C.
Mathematical Theory of Optimal Processes
Mathematical Theory of Optimal Processes is a foundational work in control theory that systematically develops the mathematical principles of optimal control, including what is now known as Pontryagin’s maximum principle.
-
D.
St. Petersburg paradox
The St. Petersburg paradox is a famous problem in probability theory and economics that highlights how a lottery with an infinite expected payoff can still attract only a finite price from rational gamblers, challenging traditional notions of expected value and decision-making under risk.
-
E.
Hamilton’s maximum principle
Hamilton’s maximum principle is a fundamental analytical tool in geometric analysis that extends the classical maximum principle to tensor-valued quantities, playing a key role in studying the behavior of solutions to the Ricci flow and related geometric evolution 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: Merton’s portfolio problem Triple: [Robert C. Merton, notableIdea, Merton’s portfolio problem]
Generated description
Merton’s portfolio problem is a foundational continuous-time optimization model in financial economics that determines an investor’s optimal consumption and investment strategy under uncertainty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Merton’s portfolio problem Target entity description: Merton’s portfolio problem is a foundational continuous-time optimization model in financial economics that determines an investor’s optimal consumption and investment strategy under uncertainty.
-
A.
Foundations of a General Theory of Sequential Decision Functions
Foundations of a General Theory of Sequential Decision Functions is a seminal work in statistics that established the mathematical foundations of sequential analysis and optimal decision-making under uncertainty.
-
B.
Introduction to Stochastic Control Theory
Introduction to Stochastic Control Theory is a foundational textbook that systematically develops the theory and methods for controlling dynamical systems under uncertainty using probabilistic and stochastic-process tools.
-
C.
Mathematical Theory of Optimal Processes
Mathematical Theory of Optimal Processes is a foundational work in control theory that systematically develops the mathematical principles of optimal control, including what is now known as Pontryagin’s maximum principle.
-
D.
St. Petersburg paradox
The St. Petersburg paradox is a famous problem in probability theory and economics that highlights how a lottery with an infinite expected payoff can still attract only a finite price from rational gamblers, challenging traditional notions of expected value and decision-making under risk.
-
E.
Hamilton’s maximum principle
Hamilton’s maximum principle is a fundamental analytical tool in geometric analysis that extends the classical maximum principle to tensor-valued quantities, playing a key role in studying the behavior of solutions to the Ricci flow and related geometric evolution equations.
- 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_69f4592fa9a48190a0450e3d0c57c4d3 |
completed | May 1, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69f4645ef63881909b46937f73d637a3 |
completed | May 1, 2026, 8:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f465be4db08190882898a17d077019 |
completed | May 1, 2026, 8:35 a.m. |
Created at: April 8, 2026, 9:45 p.m.