Triple

T21088076
Position Surface form Disambiguated ID Type / Status
Subject Howard Raiffa E519555 entity
Predicate notableWork P4 FINISHED
Object Applied Statistical Decision Theory
Applied Statistical Decision Theory is a foundational book in Bayesian decision theory that systematically develops statistical decision-making under uncertainty using probabilistic and utility-based frameworks.
E1466539 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: Applied Statistical Decision Theory | Statement: [Howard Raiffa, notableWork, Applied Statistical Decision Theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Applied Statistical Decision Theory
Context triple: [Howard Raiffa, notableWork, Applied Statistical Decision Theory]
  • A. Statistical Decision Functions
    Statistical Decision Functions is a foundational work in decision theory and statistics that systematically develops the theory of optimal decision-making under uncertainty.
  • B. 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.
  • C. Neyman–Pearson theory of hypothesis testing
    The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
  • D. decision theory
    Decision theory is a field that studies how individuals and agents should make choices under conditions of uncertainty, weighing probabilities, outcomes, and preferences to determine optimal decisions.
  • E. Sequential Analysis
    Sequential Analysis is a foundational statistical methodology that develops procedures for evaluating data as it is collected, allowing decisions to be made at variable sample sizes rather than after a fixed number of observations.
  • 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: Applied Statistical Decision Theory
Triple: [Howard Raiffa, notableWork, Applied Statistical Decision Theory]
Generated description
Applied Statistical Decision Theory is a foundational book in Bayesian decision theory that systematically develops statistical decision-making under uncertainty using probabilistic and utility-based frameworks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Applied Statistical Decision Theory
Target entity description: Applied Statistical Decision Theory is a foundational book in Bayesian decision theory that systematically develops statistical decision-making under uncertainty using probabilistic and utility-based frameworks.
  • A. Statistical Decision Functions
    Statistical Decision Functions is a foundational work in decision theory and statistics that systematically develops the theory of optimal decision-making under uncertainty.
  • B. 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.
  • C. Neyman–Pearson theory of hypothesis testing
    The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
  • D. decision theory
    Decision theory is a field that studies how individuals and agents should make choices under conditions of uncertainty, weighing probabilities, outcomes, and preferences to determine optimal decisions.
  • E. Sequential Analysis
    Sequential Analysis is a foundational statistical methodology that develops procedures for evaluating data as it is collected, allowing decisions to be made at variable sample sizes rather than after a fixed number of observations.
  • 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094cebe08190bb10f51a45c244ec completed April 21, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a095a560a508190b4e69a73e6302836 completed May 17, 2026, 6:04 a.m.
NEDg Description generation batch_6a095c58689481909fb5ab261870e7e6 completed May 17, 2026, 6:12 a.m.
NED2 Entity disambiguation (via description) batch_6a095d21b59881909898c9581fc21ba7 completed May 17, 2026, 6:16 a.m.
Created at: April 16, 2026, 2:50 p.m.