Triple
T16614199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexei Kitaev |
E403650
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Kitaev quantum phase estimation algorithm
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.
|
E1223602
|
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: Kitaev quantum phase estimation algorithm | Statement: [Alexei Kitaev, notableWork, Kitaev quantum phase estimation algorithm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitaev quantum phase estimation algorithm Context triple: [Alexei Kitaev, notableWork, Kitaev quantum phase estimation algorithm]
-
A.
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.
-
B.
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.
-
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 Complexity of Quantum States and Transformations
"The Complexity of Quantum States and Transformations" is a highly cited research paper by Scott Aaronson that investigates the computational complexity and limitations of describing, preparing, and manipulating quantum states and operations.
- 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: Kitaev quantum phase estimation algorithm Triple: [Alexei Kitaev, notableWork, Kitaev quantum phase estimation algorithm]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kitaev quantum phase estimation algorithm Target entity description: 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.
-
A.
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.
-
B.
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.
-
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 Complexity of Quantum States and Transformations
"The Complexity of Quantum States and Transformations" is a highly cited research paper by Scott Aaronson that investigates the computational complexity and limitations of describing, preparing, and manipulating quantum states and operations.
- 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_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_6a0075aeaa9881908bdef0f9f2b52e60 |
completed | May 10, 2026, 12:10 p.m. |
| NEDg | Description generation | batch_6a007705f57881908b07a20ae8957c64 |
completed | May 10, 2026, 12:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007b18f0b08190a9ddc6ad7358d6b8 |
completed | May 10, 2026, 12:33 p.m. |
Created at: April 10, 2026, 5:17 a.m.