Triple
T4593865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Taunus V4 engine |
E103560
|
entity |
| Predicate | torqueOutputRange |
P5895
|
FINISHED |
| Object | approximately 80 Nm to 130 Nm |
—
|
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: approximately 80 Nm to 130 Nm | Statement: [Ford Taunus V4 engine, torqueOutputRange, approximately 80 Nm to 130 Nm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: torqueOutputRange Context triple: [Ford Taunus V4 engine, torqueOutputRange, approximately 80 Nm to 130 Nm]
-
A.
torque
chosen
Indicates a rotational force applied by one entity on another around a pivot or axis.
-
B.
powerOutputRpm
Indicates the relationship between a system’s power output and the rotational speed (in revolutions per minute) at which that power is produced.
-
C.
heatOutputRange
Indicates the range of heat energy or thermal power that an entity can produce or emit under specified conditions.
-
D.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
E.
designPowerOutput
Indicates the intended or specified power output level that something is designed to produce under defined conditions.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd593e115081909b11149e02fe4ef3 |
completed | March 20, 2026, 2:27 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.