Triple
T8178410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | inDrive |
E190997
|
entity |
| Predicate | hasRatingSystem |
P16816
|
FINISHED |
| Object | driver rating |
—
|
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: driver rating | Statement: [inDrive, hasRatingSystem, driver rating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRatingSystem Context triple: [inDrive, hasRatingSystem, driver rating]
-
A.
hasScoreSystem
Indicates that an entity uses, is governed by, or is associated with a particular scoring or rating system.
-
B.
ratingSystem
chosen
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
-
C.
hasRatingLevel
Indicates that an entity is associated with a particular rating level or score category.
-
D.
hasRankingUnit
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
-
E.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4abb66bc81908d758c7af2e23ac6 |
completed | March 31, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:40 p.m.