Triple
T405829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tesla Model X |
E9380
|
entity |
| Predicate | safetyRating |
P8710
|
FINISHED |
| Object | high safety ratings from NHTSA |
—
|
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: high safety ratings from NHTSA | Statement: [Tesla Model X, safetyRating, high safety ratings from NHTSA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRating Context triple: [Tesla Model X, safetyRating, high safety ratings from NHTSA]
-
A.
securityFeature
Indicates that an entity provides, embodies, or is associated with a mechanism or property intended to enhance safety, protection, or defense against threats or vulnerabilities.
-
B.
rating
chosen
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
C.
estimatedStrength
Indicates that a value represents an approximate or inferred level, magnitude, or intensity of something rather than a precisely measured strength.
-
D.
hasHazardSignage
Indicates that appropriate warning or hazard signs are present to alert people to potential dangers associated with the entity.
-
E.
speedClass
Indicates the categorical speed level or range assigned to an entity based on how fast it moves or operates.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecbc00508190bbb602179273f29c |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e971a3a481909e6b075f25dd234a |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.