Triple
T36115008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota MR2 |
E1044594
|
entity |
| Predicate | secondGenerationChassisCode |
P44383
|
FINISHED |
| Object | W20 |
—
|
NE NERFINISHED |
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: W20 | Statement: [Toyota MR2, secondGenerationChassisCode, W20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondGenerationChassisCode Context triple: [Toyota MR2, secondGenerationChassisCode, W20]
-
A.
chassisCode
chosen
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
B.
predecessorChassisCode
Indicates that one chassis code directly precedes another in a chronological or generational sequence.
-
C.
secondGenerationCode
Indicates that the subject is a second-generation version or iteration of a codebase, derived from and improving upon an earlier generation.
-
D.
secondGenerationBodyStyle
Indicates that the subject has or is associated with the second generation of a particular body style.
-
E.
secondGeneration
Indicates that one entity belongs to the second generation relative to another, such as being the child of a first-generation member in a lineage or sequence.
- 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_69ff53389a0481908b2baeb43c6294f0 |
completed | May 9, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69ff52e2b4b88190b38d160d771fe14b |
completed | May 9, 2026, 3:29 p.m. |
Created at: May 3, 2026, 4:08 p.m.