Triple
T36437482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelby GT500 (2020–2022) |
E897626
|
entity |
| Predicate | coolingSystemFeatures |
P185498
|
FINISHED |
| Object | larger intercooler |
—
|
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: larger intercooler | Statement: [Shelby GT500 (2020–2022), coolingSystemFeatures, larger intercooler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coolingSystemFeatures Context triple: [Shelby GT500 (2020–2022), coolingSystemFeatures, larger intercooler]
-
A.
hasAirCooling
Indicates that an entity is equipped with or utilizes an air-based cooling system.
-
B.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
-
C.
hasCoolingFlow
Indicates that an entity is equipped with or utilizes a system or mechanism to remove heat or maintain a lower temperature through the flow of a cooling medium.
-
D.
coolingStyle
Indicates the method or mechanism by which something is cooled or has its temperature reduced.
-
E.
hasCoolingCore
Indicates that an entity possesses a central region or core characterized by cooling or lower temperature relative to its surroundings.
- 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_69f76e56636481908eda808ab0273401 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.