Triple
T20512663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | speedup theorem |
E503602
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Blum complexity axioms |
—
|
NE NERFINISHED |
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: Blum complexity axioms | Statement: [speedup theorem, relatedTo, Blum complexity axioms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blum complexity axioms Context triple: [speedup theorem, relatedTo, Blum complexity axioms]
-
A.
Blum complexity measures
Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
-
B.
Blum axioms
chosen
Blum axioms are a set of formal conditions introduced by Manuel Blum that rigorously define what constitutes a valid complexity measure in computational complexity theory.
-
C.
The Knowledge Complexity of Interactive Proof Systems
"The Knowledge Complexity of Interactive Proof Systems" is a seminal theoretical computer science paper that introduced the notion of zero-knowledge proofs, fundamentally shaping modern cryptography and complexity theory.
-
D.
Blum–Shub–Smale model of computation
The Blum–Shub–Smale model of computation is a theoretical framework for analyzing algorithms over real numbers, extending classical complexity theory beyond discrete computation.
-
E.
“Probabilistic computations: Toward a unified measure of complexity”
“Probabilistic computations: Toward a unified measure of complexity” is a seminal research paper by Andrew Yao that laid foundational concepts in computational complexity theory, particularly regarding the role and analysis of randomness in algorithms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcd74c48190b050e25c20154c09 |
completed | April 20, 2026, 9:42 p.m. |
Created at: April 16, 2026, 11:36 a.m.