Triple

T15502674
Position Surface form Disambiguated ID Type / Status
Subject Mathematical Foundations of Information Theory E378999 entity
Predicate subject P450 FINISHED
Object Shannon information theory E158223 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 information theory | Statement: [Mathematical Foundations of Information Theory, subject, Shannon information theory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shannon information theory
Context triple: [Mathematical Foundations of Information Theory, subject, Shannon information theory]
  • A. 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.
  • B. 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.
  • C. information theory chosen
    Information theory is a mathematical framework for quantifying information, communication, and data compression, foundational to modern digital communication and signal processing.
  • D. 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.
  • E. Coding and Information Theory
    "Coding and Information Theory" is a foundational textbook by Richard W. Hamming that introduces the mathematical principles underlying error-correcting codes and the transmission of information.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcc5bb88190b8a9a81419a9a38b completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3669f908819087162b1b8a4e4320 completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:54 a.m.