Triple
T14860129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsch–Jozsa algorithm |
E349464
|
entity |
| Predicate | modelOfComputation |
P37649
|
FINISHED |
| Object | quantum circuit model |
—
|
LITERAL 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: quantum circuit model | Statement: [Deutsch–Jozsa algorithm, modelOfComputation, quantum circuit model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelOfComputation Context triple: [Deutsch–Jozsa algorithm, modelOfComputation, quantum circuit model]
-
A.
computingModel
chosen
Indicates the computational framework, paradigm, or formal system used to perform or describe a computation.
-
B.
computationalClass
Indicates that two entities share the same computational complexity class or that one entity is categorized within a specified computational complexity class.
-
C.
computes
Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
-
D.
computationInput
Indicates that an entity serves as input data or parameters consumed by a computation or processing activity.
-
E.
turingComplete
Indicates that a system or language is capable of performing any computation that a universal Turing machine can, given enough time and memory.
- F. None of above.
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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.