Triple
T22797627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PC Zone |
E564291
|
entity |
| Predicate | reviewScoringSystem |
P146607
|
FINISHED |
| Object | percentage score |
—
|
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: percentage score | Statement: [PC Zone, reviewScoringSystem, percentage score]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reviewScoringSystem Context triple: [PC Zone, reviewScoringSystem, percentage score]
-
A.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
-
B.
reviewScale
chosen
Indicates the rating system or range (such as 1–5 stars, 0–10, etc.) used to evaluate or score something in a review.
-
C.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
D.
ratingSystemType
Indicates the classification or scheme used to define how ratings are structured, interpreted, or applied within a given context.
-
E.
featuresScoringSystem
Indicates that one entity incorporates or provides a particular scoring or rating system as part of its functionality or design.
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cda76448190891c5190e1d75ae0 |
completed | April 29, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:30 p.m.