Triple
T31131619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amiga accelerator boards |
E793522
|
entity |
| Predicate | improve |
P161052
|
FINISHED |
| Object | CPU-intensive applications performance |
—
|
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: CPU-intensive applications performance | Statement: [Amiga accelerator boards, improve, CPU-intensive applications performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: improve Context triple: [Amiga accelerator boards, improve, CPU-intensive applications performance]
-
A.
improvesIn
chosen
Indicates that one entity causes or contributes to an increase in quality, performance, or effectiveness in another entity or context.
-
B.
improvesOn
Indicates that one entity enhances, refines, or performs better than another entity, typically by addressing its limitations or increasing its effectiveness.
-
C.
seeksToImprove
Indicates an intentional effort by one entity to make another entity or condition better than its current state.
-
D.
improvementFocus
Indicates that an entity is specifically directed toward or concerned with making improvements to another entity or aspect.
-
E.
hasImproved
Indicates that an entity’s state, quality, or performance has become better compared to a previous point in time.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:05 p.m.