Triple
T24553231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honda Sensing |
E607431
|
entity |
| Predicate | oftenStandardOn |
P98539
|
FINISHED |
| Object | higher trims of Honda vehicles |
—
|
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 trims of Honda vehicles | Statement: [Honda Sensing, oftenStandardOn, higher trims of Honda vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenStandardOn Context triple: [Honda Sensing, oftenStandardOn, higher trims of Honda vehicles]
-
A.
isStandardOn
chosen
Indicates that a particular feature, option, or component is included by default as part of another item, rather than being optional or extra.
-
B.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
C.
oftenSetIn
Indicates that something, such as a story or event, frequently takes place within a particular setting or context.
-
D.
oftenStatedWith
Indicates that one statement, fact, or expression is frequently mentioned or asserted together with another.
-
E.
usesStandard
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cf1ef88190977da0fb79796616 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.