Triple

T11560423
Position Surface form Disambiguated ID Type / Status
Subject Harald Cramér E274126 entity
Predicate knownFor P22 FINISHED
Object Cramér–Lundberg model in risk theory
The Cramér–Lundberg model in risk theory is a classical stochastic model used in actuarial science to describe an insurer’s surplus over time, analyzing ruin probabilities based on premium income and random claim arrivals.
E933487 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: Cramér–Lundberg model in risk theory | Statement: [Harald Cramér, knownFor, Cramér–Lundberg model in risk theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cramér–Lundberg model in risk theory
Context triple: [Harald Cramér, knownFor, Cramér–Lundberg model in risk theory]
  • A. Tirpitz risk theory
    Tirpitz risk theory was a pre–World War I German naval strategy asserting that building a powerful battle fleet would deter Britain by making any conflict at sea too risky for the Royal Navy.
  • B. Modern Probability Theory and Its Applications
    "Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
  • C. Khinchin–Pollaczek formula
    The Khinchin–Pollaczek formula is a result in probability theory and queueing theory that provides an explicit expression for the stationary waiting-time distribution in certain single-server queues.
  • D. Act on Non-Life Insurance Rating Organizations of Japan
    The Act on Non-Life Insurance Rating Organizations of Japan is a Japanese law that regulates the establishment and operation of rating organizations that calculate and provide standard premium rates for non-life insurance.
  • E. Limit Laws for Sums of Independent Random Variables
    Limit Laws for Sums of Independent Random Variables is a foundational mathematical work that systematically develops the theory of probability limit theorems, including results such as the law of large numbers and central limit behavior for sums of independent random variables.
  • 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: Cramér–Lundberg model in risk theory
Triple: [Harald Cramér, knownFor, Cramér–Lundberg model in risk theory]
Generated description
The Cramér–Lundberg model in risk theory is a classical stochastic model used in actuarial science to describe an insurer’s surplus over time, analyzing ruin probabilities based on premium income and random claim arrivals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cramér–Lundberg model in risk theory
Target entity description: The Cramér–Lundberg model in risk theory is a classical stochastic model used in actuarial science to describe an insurer’s surplus over time, analyzing ruin probabilities based on premium income and random claim arrivals.
  • A. Tirpitz risk theory
    Tirpitz risk theory was a pre–World War I German naval strategy asserting that building a powerful battle fleet would deter Britain by making any conflict at sea too risky for the Royal Navy.
  • B. Modern Probability Theory and Its Applications
    "Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
  • C. Khinchin–Pollaczek formula
    The Khinchin–Pollaczek formula is a result in probability theory and queueing theory that provides an explicit expression for the stationary waiting-time distribution in certain single-server queues.
  • D. Act on Non-Life Insurance Rating Organizations of Japan
    The Act on Non-Life Insurance Rating Organizations of Japan is a Japanese law that regulates the establishment and operation of rating organizations that calculate and provide standard premium rates for non-life insurance.
  • E. Limit Laws for Sums of Independent Random Variables
    Limit Laws for Sums of Independent Random Variables is a foundational mathematical work that systematically develops the theory of probability limit theorems, including results such as the law of large numbers and central limit behavior for sums of independent random variables.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a899d4481909a3bce3147763b51 completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e88b84d48190948243646bb5fd2b completed April 21, 2026, 3:01 a.m.
NEDg Description generation batch_69e6ef951eb881909810b5923385c4c6 completed April 21, 2026, 3:31 a.m.
NED2 Entity disambiguation (via description) batch_69e6f92ed97c819081576add624dcc27 completed April 21, 2026, 4:12 a.m.
Created at: April 8, 2026, 9:37 p.m.