Triple
T12591900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Prix GXP |
E300625
|
entity |
| Predicate | hasExhaust |
P85175
|
FINISHED |
| Object | performance exhaust system |
—
|
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: performance exhaust system | Statement: [Grand Prix GXP, hasExhaust, performance exhaust system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExhaust Context triple: [Grand Prix GXP, hasExhaust, performance exhaust system]
-
A.
hasRemainsOf
Indicates that one entity physically contains, preserves, or is associated with the leftover physical traces or remnants of another entity.
-
B.
hasExits
Indicates that an entity provides one or more ways out or routes leading from it to other locations or states.
-
C.
hasPartUsed
chosen
Indicates that an entity utilizes another entity as a component or constituent part in its structure, function, or operation.
-
D.
hasBurnUnit
Indicates that one entity (typically a medical facility) includes or is equipped with a specialized unit dedicated to the treatment and care of burn patients.
-
E.
hasComb
Indicates that an entity possesses or is equipped with a comb.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:07 p.m.