Triple
T29999121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virtua Racing Deluxe |
E762111
|
entity |
| Predicate | improvementDetail |
P163633
|
FINISHED |
| Object | higher detail car models |
—
|
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: higher detail car models | Statement: [Virtua Racing Deluxe, improvementDetail, higher detail car models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: improvementDetail Context triple: [Virtua Racing Deluxe, improvementDetail, higher detail car models]
-
A.
improvesIn
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.
guidanceImprovement
Indicates that one entity provides direction, feedback, or support that helps another entity enhance or improve its performance, behavior, or outcomes.
-
D.
improvementFocus
chosen
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_69f2246a47ac81909cf5213053687ffc |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6794cf5848190a60ca2c4d9f50098 |
completed | May 2, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69f66ec9919881908a187bfc7c4df192 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:40 p.m.