Triple

T16614200
Position Surface form Disambiguated ID Type / Status
Subject Alexei Kitaev E403650 entity
Predicate notableWork P4 FINISHED
Object Kitaev’s phase estimation algorithm E1223602 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: Kitaev’s phase estimation algorithm | Statement: [Alexei Kitaev, notableWork, Kitaev’s phase estimation algorithm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kitaev’s phase estimation algorithm
Context triple: [Alexei Kitaev, notableWork, Kitaev’s phase estimation algorithm]
  • A. Kitaev quantum phase estimation algorithm chosen
    The Kitaev quantum phase estimation algorithm is a foundational quantum computing procedure introduced by Alexei Kitaev that efficiently extracts eigenphase information of unitary operators, underpinning many quantum algorithms such as Shor’s factoring algorithm.
  • B. Grover’s algorithm
    Grover’s algorithm is a quantum search algorithm that provides a quadratic speedup over classical methods for finding a marked item in an unsorted database.
  • C. Bernstein–Vazirani algorithm
    The Bernstein–Vazirani algorithm is a quantum algorithm that efficiently determines a hidden binary string using a single query to an oracle, illustrating quantum speedup over classical methods.
  • D. Deutsch–Jozsa algorithm
    The Deutsch–Jozsa algorithm is a foundational quantum algorithm that demonstrates how quantum computation can solve certain decision problems exponentially faster than any classical deterministic algorithm.
  • E. The Learnability of Quantum States
    "The Learnability of Quantum States" is a research paper by Scott Aaronson that investigates under what conditions quantum states can be efficiently learned or approximated from measurement data within the framework of computational learning theory.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e360983d2c8190b1fe7f18aedfbde1 completed April 18, 2026, 10:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007dad10ec8190b41d82b38fcd4dae completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.