Triple
T15790270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercedes-Benz E 200 |
E382845
|
entity |
| Predicate | comfortFocus |
P120024
|
FINISHED |
| Object | ride comfort |
—
|
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: ride comfort | Statement: [Mercedes-Benz E 200, comfortFocus, ride comfort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comfortFocus Context triple: [Mercedes-Benz E 200, comfortFocus, ride comfort]
-
A.
relativeComfort
Indicates a comparative relationship where one entity is judged to be more or less comfortable than another under given conditions.
-
B.
relief
Indicates a state or action in which distress, pain, or difficulty is reduced, eased, or removed for an entity.
-
C.
relievedBy
Indicates that one entity eases, reduces, or removes the burden, pain, stress, or responsibility experienced by another entity.
-
D.
hasRelaxation
Indicates that one entity provides or is associated with a relaxation, easing, or reduction of constraints, tension, or strictness in relation to another entity.
-
E.
hasRelief
Indicates that one entity features or exhibits a raised or sculpted surface design (relief) in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e006b17f7881908b8c7a37f0af4581 |
completed | April 15, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:48 a.m.