Triple

T990926
Position Surface form Disambiguated ID Type / Status
Subject Manuel Blum E21386 entity
Predicate notableWork P4 FINISHED
Object 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.
E117702 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: Blum complexity measures | Statement: [Manuel Blum, notableWork, Blum complexity measures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blum complexity measures
Context triple: [Manuel Blum, notableWork, Blum complexity measures]
  • A. 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.
  • B. Randomness and Computation
    "Randomness and Computation" is Shafi Goldwasser's influential doctoral thesis that helped lay the foundations of modern complexity theory and cryptography by rigorously exploring the role of randomness in efficient computation.
  • C. Interactive Proofs and the Hardness of Approximating Cliques
    "Interactive Proofs and the Hardness of Approximating Cliques" is a seminal theoretical computer science paper that introduced powerful interactive proof techniques to show that finding near-maximum cliques in graphs is computationally intractable to approximate within strong bounds.
  • D. PCP theorem
    The PCP theorem is a fundamental result in computational complexity theory stating that every problem in NP has probabilistically checkable proofs that can be verified by examining only a constant number of bits, with major implications for the hardness of approximation.
  • E. Proceedings of the Seventeenth Annual ACM Symposium on Theory of Computing
    Proceedings of the Seventeenth Annual ACM Symposium on Theory of Computing is a 1985 ACM conference volume collecting influential research papers in theoretical computer science, including foundational work on topics such as interactive proof systems and computational complexity.
  • 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: Blum complexity measures
Triple: [Manuel Blum, notableWork, Blum complexity measures]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blum complexity measures
Target entity description: 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.
  • A. 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.
  • B. Randomness and Computation
    "Randomness and Computation" is Shafi Goldwasser's influential doctoral thesis that helped lay the foundations of modern complexity theory and cryptography by rigorously exploring the role of randomness in efficient computation.
  • C. Interactive Proofs and the Hardness of Approximating Cliques
    "Interactive Proofs and the Hardness of Approximating Cliques" is a seminal theoretical computer science paper that introduced powerful interactive proof techniques to show that finding near-maximum cliques in graphs is computationally intractable to approximate within strong bounds.
  • D. PCP theorem
    The PCP theorem is a fundamental result in computational complexity theory stating that every problem in NP has probabilistically checkable proofs that can be verified by examining only a constant number of bits, with major implications for the hardness of approximation.
  • E. Proceedings of the Seventeenth Annual ACM Symposium on Theory of Computing
    Proceedings of the Seventeenth Annual ACM Symposium on Theory of Computing is a 1985 ACM conference volume collecting influential research papers in theoretical computer science, including foundational work on topics such as interactive proof systems and computational complexity.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4ac27e081908f132115464667b2 completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac258d9f4c8190b285455410b30575 completed March 7, 2026, 1:18 p.m.
NEDg Description generation batch_69ac267e4fa08190895fa6809d0decb8 completed March 7, 2026, 1:22 p.m.
NED2 Entity disambiguation (via description) batch_69ac271c8ad081909c1f1629e0793c40 completed March 7, 2026, 1:24 p.m.
Created at: March 1, 2026, 7:41 p.m.