Triple
T9010123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamborghini Urus |
E215445
|
entity |
| Predicate | 0To100KphTime |
P45714
|
FINISHED |
| Object | about 3.6 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: about 3.6 seconds | Statement: [Lamborghini Urus, 0To100KphTime, about 3.6 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 0To100KphTime Context triple: [Lamborghini Urus, 0To100KphTime, about 3.6 seconds]
-
A.
acceleration0To100Kmh
chosen
Indicates the rate or time it takes for something to accelerate from 0 to 100 kilometers per hour.
-
B.
hasRunSub10Seconds100m
Indicates that the subject has completed a 100-meter sprint in under 10 seconds.
-
C.
acceleration0To60mph
Indicates the rate or time it takes for something to increase its speed from 0 to 60 miles per hour.
-
D.
timeEquivalentOf
Indicates that two temporal entities represent the same point in time or duration, possibly expressed in different formats or units.
-
E.
category2UpperBound_mph
Indicates the maximum speed in miles per hour that defines the upper limit of category 2 in a categorized range or scale.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c00ae8819090786385a72e8baf |
completed | April 1, 2026, 12:41 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:06 p.m.