Triple

T7150360
Position Surface form Disambiguated ID Type / Status
Subject Nyquist theorem E166675 entity
Predicate extendedBy P9926 FINISHED
Object Shannon’s information theory E1169 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: Shannon’s information theory | Statement: [Nyquist theorem, extendedBy, Shannon’s information theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shannon’s information theory
Context triple: [Nyquist theorem, extendedBy, Shannon’s information theory]
  • A. A Mathematical Theory of Communication chosen
    A Mathematical Theory of Communication is Claude Shannon’s landmark 1948 paper that founded information theory by rigorously defining concepts like information, entropy, and channel capacity.
  • B. Mathematical Foundations of Information Theory
    Mathematical Foundations of Information Theory is a seminal monograph by Aleksandr Khinchin that rigorously develops the probabilistic and mathematical basis of Shannon’s information theory.
  • C. An Introduction to Information Theory: Symbols, Signals and Noise
    An Introduction to Information Theory: Symbols, Signals and Noise is a classic, accessible textbook that explains the fundamental concepts of information theory, communication, and coding for a broad scientific and engineering audience.
  • D. Elements of Information Theory
    Elements of Information Theory is a foundational textbook that systematically develops the theory and applications of information theory, widely used in communications, coding, and data science.
  • E. Slepian–Wolf coding theorem
    The Slepian–Wolf coding theorem is a fundamental result in information theory that characterizes the limits of lossless data compression for correlated sources encoded separately but decoded jointly.
  • 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_69c68886779c8190a8e3fbabffe68253 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7f28b188190b1732ca711666531 completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ada940e08190b16e97e363801e75 completed March 28, 2026, 10:30 a.m.
Created at: March 27, 2026, 2:46 p.m.