Triple

T3572448
Position Surface form Disambiguated ID Type / Status
Subject Born rule E75605 entity
Predicate alsoKnownAs P39 FINISHED
Object Born statistical interpretation
The Born statistical interpretation is the quantum-mechanical view that a system’s wave function encodes probabilities for measurement outcomes rather than definite physical properties.
E368818 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: Born statistical interpretation | Statement: [Born rule, alsoKnownAs, Born statistical interpretation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Born statistical interpretation
Context triple: [Born rule, alsoKnownAs, Born statistical interpretation]
  • A. A Treatise on Probability
    A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
  • B. Statistical Methods for Research Workers
    Statistical Methods for Research Workers is a foundational 1925 statistics textbook by Ronald A. Fisher that helped establish modern statistical theory and practice in scientific research.
  • C. Laplace law of error
    The Laplace law of error is a probability distribution characterized by a sharp peak at the mean and heavier tails than the normal distribution, historically used to model the magnitude of observational errors.
  • D. Gaussian law of error
    The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
  • E. The Principles of Statistical Mechanics
    The Principles of Statistical Mechanics is a classic 1938 textbook by Richard C. Tolman that systematically develops the foundations of statistical mechanics and its applications to thermodynamics and physical chemistry.
  • 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: Born statistical interpretation
Triple: [Born rule, alsoKnownAs, Born statistical interpretation]
Generated description
The Born statistical interpretation is the quantum-mechanical view that a system’s wave function encodes probabilities for measurement outcomes rather than definite physical properties.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Born statistical interpretation
Target entity description: The Born statistical interpretation is the quantum-mechanical view that a system’s wave function encodes probabilities for measurement outcomes rather than definite physical properties.
  • A. A Treatise on Probability
    A Treatise on Probability is John Maynard Keynes’s influential 1921 work that develops a logical and philosophical theory of probability, challenging classical and frequency-based interpretations.
  • B. Statistical Methods for Research Workers
    Statistical Methods for Research Workers is a foundational 1925 statistics textbook by Ronald A. Fisher that helped establish modern statistical theory and practice in scientific research.
  • C. Laplace law of error
    The Laplace law of error is a probability distribution characterized by a sharp peak at the mean and heavier tails than the normal distribution, historically used to model the magnitude of observational errors.
  • D. Gaussian law of error
    The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
  • E. The Principles of Statistical Mechanics
    The Principles of Statistical Mechanics is a classic 1938 textbook by Richard C. Tolman that systematically develops the foundations of statistical mechanics and its applications to thermodynamics and physical chemistry.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0c447fc81909689259558187af4 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbbcf2d08190901049948df66f0c completed March 13, 2026, 7:24 a.m.
NEDg Description generation batch_69b3bca07cac81908253b2b4225f3d67 completed March 13, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69b3f5b6e66c81908700d5f3df0a864d completed March 13, 2026, 11:32 a.m.
Created at: March 8, 2026, 3:21 p.m.