Triple
T8471381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Paint |
E200287
|
entity |
| Predicate | complexityLevel |
P2406
|
FINISHED |
| Object | basic |
—
|
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: basic | Statement: [Microsoft Paint, complexityLevel, basic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: complexityLevel Context triple: [Microsoft Paint, complexityLevel, basic]
-
A.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
B.
difficulty
chosen
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
C.
intelligenceLevel
Indicates the degree or measure of cognitive ability or intelligence attributed to an entity.
-
D.
hasReasoningComplexity
Indicates that an action, process, or decision involves a certain level or type of cognitive or logical complexity in its reasoning.
-
E.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f3a81881908f20514579945ffa |
completed | March 31, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69cbd10072cc819084be1ed9ac7ebe9d |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:11 p.m.