Triple
T4279375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B-tree |
E97112
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | B# tree |
E97112
|
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: B# tree | Statement: [B-tree, hasVariant, B# tree]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: B# tree Context triple: [B-tree, hasVariant, B# tree]
-
A.
B-tree
chosen
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.
-
B.
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.
-
C.
Bo tree
The Bo tree is the sacred fig tree under which Siddhartha Gautama is believed to have attained enlightenment, making it a central symbol in Buddhism.
-
D.
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.
-
E.
Merkle tree
A Merkle tree is a cryptographic data structure that uses a tree of hash values to efficiently and securely verify the integrity and consistency of large sets of data.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350367da48190b735deef9b5d2d2e |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b708b481908c1683741f84ee55 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.