Triple
T36115009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota MR2 |
E1044594
|
entity |
| Predicate | thirdGenerationChassisCode |
P44383
|
FINISHED |
| Object | W30 |
—
|
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: W30 | Statement: [Toyota MR2, thirdGenerationChassisCode, W30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdGenerationChassisCode Context triple: [Toyota MR2, thirdGenerationChassisCode, W30]
-
A.
chassisCode
chosen
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
B.
thirdGenerationBodyStyle
Indicates that the subject has the body style corresponding to the third generation of a particular model or design series.
-
C.
thirdGeneration
Indicates that one entity is the grandchild (third generation) relative to another entity in a lineage or succession.
-
D.
predecessorChassisCode
Indicates that one chassis code directly precedes another in a chronological or generational sequence.
-
E.
thirdGenerationEngine
Indicates that the engine belongs to the third generation in a defined sequence of engine designs or technological iterations.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: May 3, 2026, 4:08 p.m.