pairing heap (as a practical alternative)
E1045596
comparison-based priority queue
heap data structure
priority queue implementation
self-adjusting heap
A pairing heap is a simple, self-adjusting heap data structure that offers efficient practical performance for priority queue operations and is often used as an alternative to more complex structures like Fibonacci heaps.
All labels observed (1)
| Label | Occurrences |
|---|---|
| pairing heap (as a practical alternative) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13507223 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: pairing heap (as a practical alternative) Context triple: [Fibonacci heap, hasVariant, pairing heap (as a practical alternative)]
-
A.
Fibonacci heap
A Fibonacci heap is an advanced data structure for implementing priority queues that supports very fast amortized running times for operations like insert and decrease-key, making it useful in algorithms such as Dijkstra’s shortest path.
-
B.
Heapsort
Heapsort is a comparison-based sorting algorithm that uses a binary heap data structure to sort elements in-place with O(n log n) time complexity and O(1) auxiliary space.
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C.
Heap
Heap is the surname of Imogen Heap, an English singer-songwriter, producer, and audio engineer known for her innovative electronic music and vocal processing.
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D.
union–find data structure
The union–find data structure is an efficient algorithmic structure that maintains disjoint sets and supports fast union and find operations, widely used in graph algorithms such as Kruskal’s minimum spanning tree.
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E.
splay tree
A splay tree is a self-adjusting binary search tree data structure that moves frequently accessed elements closer to the root to optimize average access time.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: pairing heap (as a practical alternative) Target entity description: A pairing heap is a simple, self-adjusting heap data structure that offers efficient practical performance for priority queue operations and is often used as an alternative to more complex structures like Fibonacci heaps.
-
A.
Fibonacci heap
A Fibonacci heap is an advanced data structure for implementing priority queues that supports very fast amortized running times for operations like insert and decrease-key, making it useful in algorithms such as Dijkstra’s shortest path.
-
B.
Heapsort
Heapsort is a comparison-based sorting algorithm that uses a binary heap data structure to sort elements in-place with O(n log n) time complexity and O(1) auxiliary space.
-
C.
Heap
Heap is the surname of Imogen Heap, an English singer-songwriter, producer, and audio engineer known for her innovative electronic music and vocal processing.
-
D.
union–find data structure
The union–find data structure is an efficient algorithmic structure that maintains disjoint sets and supports fast union and find operations, widely used in graph algorithms such as Kruskal’s minimum spanning tree.
-
E.
splay tree
A splay tree is a self-adjusting binary search tree data structure that moves frequently accessed elements closer to the root to optimize average access time.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
comparison-based priority queue
ⓘ
heap data structure ⓘ priority queue implementation ⓘ self-adjusting heap ⓘ |
| advantageOver |
Fibonacci heap in constant factors for typical workloads
ⓘ
Fibonacci heap in implementation simplicity ⓘ |
| category |
amortized data structure
ⓘ
meldable heap ⓘ |
| comparedTo | Fibonacci heap NERFINISHED ⓘ |
| deleteMinProcess | remove minimum root and pairwise meld its children ⓘ |
| designGoal | combine simplicity with good amortized performance ⓘ |
| hasAlternativeName | pairing heap priority queue ⓘ |
| hasProperty |
amortized efficient operations
ⓘ
does not require auxiliary structural information per node ⓘ good practical performance ⓘ heap-ordered ⓘ pointer-based ⓘ self-adjusting ⓘ simple to implement ⓘ supports meldable heaps ⓘ |
| implementationDetail | usually implemented with child-sibling representation for trees ⓘ |
| introducedAs | simpler alternative to Fibonacci heap ⓘ |
| isMeldable | true ⓘ |
| linkOperation | compare two roots and make larger root a child of smaller root ⓘ |
| memoryOverhead | low compared to Fibonacci heap ⓘ |
| mergeStrategy | pairwise linking of subtrees ⓘ |
| nodeStructure | tree node with key and list of children ⓘ |
| practicalObservation | often outperforms Fibonacci heap on real workloads ⓘ |
| representation |
forest of heap-ordered trees
ⓘ
multiway tree ⓘ |
| requires | total order on keys ⓘ |
| supports | online operations ⓘ |
| supportsOperation |
decrease-key
ⓘ
delete-min ⓘ find-min ⓘ insert ⓘ meld ⓘ merge ⓘ |
| timeComplexityDecreaseKey | sub-logarithmic amortized in practice (theoretical bounds vary) ⓘ |
| timeComplexityDeleteMin | O(log n) amortized (under common analyses) ⓘ |
| timeComplexityFindMin | O(1) amortized ⓘ |
| timeComplexityInsert | O(1) amortized ⓘ |
| timeComplexityMeld | O(1) amortized ⓘ |
| typicalUseCase |
Dijkstra shortest path algorithm priority queue
ⓘ
any application needing fast decrease-key ⓘ event simulation priority queue ⓘ |
| usedAs |
implementation of priority queue abstract data type
ⓘ
practical alternative to Fibonacci heap ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: pairing heap (as a practical alternative) Description of subject: A pairing heap is a simple, self-adjusting heap data structure that offers efficient practical performance for priority queue operations and is often used as an alternative to more complex structures like Fibonacci heaps.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.