Triple
T2276843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Car Assessment Program |
E50790
|
entity |
| Predicate | maximumRating |
P29667
|
FINISHED |
| Object | 5-star 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: 5-star rating | Statement: [New Car Assessment Program, maximumRating, 5-star rating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumRating Context triple: [New Car Assessment Program, maximumRating, 5-star rating]
-
A.
maximumNumber
chosen
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
-
B.
highestRankIn
Indicates that one entity holds the top or most senior rank within a specified group, category, or context relative to other entities.
-
C.
maximumService
Indicates that an entity provides the highest allowable or achievable level of service within a given context or system.
-
D.
maximumIntensity
Indicates the greatest level or strength that a quantity, effect, or signal can reach within a given context.
-
E.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1ee22988190b7fa28b0b62e8668 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdb9aa3c819088d0316c5269a1c2 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.