Triple

T13507258
Position Surface form Disambiguated ID Type / Status
Subject splay tree E321044 entity
Predicate relatedTo P37 FINISHED
Object AVL tree
An AVL tree is a self-balancing binary search tree data structure that maintains strict height balance to ensure efficient insertion, deletion, and lookup operations.
 E1045598 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: AVL tree | Statement: [splay tree, relatedTo, AVL tree]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AVL tree
Context triple: [splay tree, relatedTo, AVL tree]
  • A. AVL
    AVL is the three-letter IATA airport code for Asheville Regional Airport serving the Asheville, North Carolina area.
  • B. BST
    BST is the time zone used throughout Bangladesh, set six hours ahead of Coordinated Universal Time (UTC+6).
  • C. BST
    BST (British Summer Time) is the daylight saving time observed in the United Kingdom, set one hour ahead of Coordinated Universal Time (UTC+1) during the summer months.
  • D. B-tree
    A B-tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, commonly used to implement database indexes.
  • 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.
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: AVL tree
Triple: [splay tree, relatedTo, AVL tree]
Generated description
An AVL tree is a self-balancing binary search tree data structure that maintains strict height balance to ensure efficient insertion, deletion, and lookup operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AVL tree
Target entity description: An AVL tree is a self-balancing binary search tree data structure that maintains strict height balance to ensure efficient insertion, deletion, and lookup operations.
  • A. AVL
    AVL is the three-letter IATA airport code for Asheville Regional Airport serving the Asheville, North Carolina area.
  • B. BST
    BST is the time zone used throughout Bangladesh, set six hours ahead of Coordinated Universal Time (UTC+6).
  • C. BST
    BST (British Summer Time) is the daylight saving time observed in the United Kingdom, set one hour ahead of Coordinated Universal Time (UTC+1) during the summer months.
  • D. B-tree
    A B-tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, commonly used to implement database indexes.
  • 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

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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf8259a08190ada13c4a3078f07d completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7548e51b881909a3384812556bc3d completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f757108e088190aeec031eccc9aca3 completed May 3, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69f757e7322c8190b0e36e8373d42ac4 completed May 3, 2026, 2:12 p.m.
Created at: April 9, 2026, 9:43 p.m.