Triple
T356710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon–Khinchin axioms |
E7559
|
entity |
| Predicate | hasAxiom |
P12252
|
FINISHED |
| Object | Shannon additivity axiom |
E1168
|
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 additivity axiom | Statement: [Shannon–Khinchin axioms, hasAxiom, Shannon additivity axiom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shannon additivity axiom Context triple: [Shannon–Khinchin axioms, hasAxiom, Shannon additivity axiom]
-
A.
Shannon–Khinchin axioms
The Shannon–Khinchin axioms are a set of fundamental conditions that uniquely characterize Shannon entropy as the standard measure of information and uncertainty in probability theory and information theory.
-
B.
Shannon entropy
chosen
Shannon entropy is a fundamental measure in information theory that quantifies the average uncertainty or information content in a random variable or message source.
-
C.
Rényi entropy
Rényi entropy is a generalized measure of information and uncertainty that extends Shannon entropy by introducing a tunable order parameter to emphasize different aspects of a probability distribution.
-
D.
Communication Theory of Secrecy Systems
Communication Theory of Secrecy Systems is Claude Shannon’s foundational paper that established the mathematical basis of modern cryptography and information-theoretic security.
-
E.
Rényi divergence
Rényi divergence is a family of information-theoretic measures that generalize Kullback–Leibler divergence to quantify the dissimilarity between probability distributions, parameterized by an order α.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ee29ede0819095279af95b53e350 |
completed | Feb. 28, 2026, 1:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e019211c819087edeb99431061fa |
completed | March 1, 2026, 6:43 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.