Triple
T10293672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koenigsegg Agera R |
E241427
|
entity |
| Predicate | 0-200kmhTime |
P92950
|
FINISHED |
| Object | around 7.8 seconds |
—
|
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: around 7.8 seconds | Statement: [Koenigsegg Agera R, 0-200kmhTime, around 7.8 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 0-200kmhTime Context triple: [Koenigsegg Agera R, 0-200kmhTime, around 7.8 seconds]
-
A.
acceleration0To100Kmh
Indicates the rate or time it takes for something to accelerate from 0 to 100 kilometers per hour.
-
B.
acceleration0To60mph
Indicates the rate or time it takes for something to increase its speed from 0 to 60 miles per hour.
-
C.
maxSpeed
Indicates the greatest possible speed at which an entity can move or operate under specified conditions.
-
D.
speedAchieved
Indicates that a particular speed has been reached or attained by an entity during an event or action.
-
E.
maximumSpeedRecord
Indicates that an entity holds the highest recorded speed value (a speed record) within a given context or category.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2d46fb08190b7694290692e47dc |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d29d7cf08190acd70cee634c5cdb |
completed | April 7, 2026, 9:47 a.m. |
Created at: April 6, 2026, 11:42 a.m.