Triple
T36151589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVL tree |
E1045598
|
entity |
| Predicate | isMoreStrictlyBalancedThan |
P90714
|
FINISHED |
| Object | red-black tree |
—
|
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: red-black tree | Statement: [AVL tree, isMoreStrictlyBalancedThan, red-black tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMoreStrictlyBalancedThan Context triple: [AVL tree, isMoreStrictlyBalancedThan, red-black tree]
-
A.
isBalanced
Indicates that the elements or parts involved are in a state of equilibrium, with no side or component outweighing or dominating the others.
-
B.
hasStricterStandardThan
chosen
Indicates that one entity’s rules, criteria, or requirements are more demanding or rigorous than those of another entity.
-
C.
isStrictWith
Indicates that one entity enforces rules, standards, or discipline firmly and without leniency toward another entity.
-
D.
isDeeperThan
Indicates that one entity has a greater depth or is positioned further down than another entity.
-
E.
isMoreCompactThan
Indicates that one entity occupies less space or volume than another, making it denser or more tightly arranged in comparison.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b3e2f3c08190be4fd1ae4fa1266d |
completed | May 3, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bcc47081909fe7d592ac69006c |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.