Triple
T5257077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nissan Altima |
E118726
|
entity |
| Predicate | featureOption |
P54721
|
FINISHED |
| Object | advanced driver-assistance systems |
—
|
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: advanced driver-assistance systems | Statement: [Nissan Altima, featureOption, advanced driver-assistance systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureOption Context triple: [Nissan Altima, featureOption, advanced driver-assistance systems]
-
A.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
B.
featuresItem
chosen
Indicates that one entity includes, presents, or highlights another entity as a notable item or component.
-
C.
featureSet
Indicates that one entity is a collection or configuration of features associated with or applied to another entity.
-
D.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
E.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcced6881909bdb7ac5471a37fe |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.