Triple
T21815907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3.4L DOHC V6 (LQ1) |
E538604
|
entity |
| Predicate | typicalTransmissionPairing |
P69696
|
FINISHED |
| Object | 4-speed automatic transmission |
—
|
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: 4-speed automatic transmission | Statement: [3.4L DOHC V6 (LQ1), typicalTransmissionPairing, 4-speed automatic transmission]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTransmissionPairing Context triple: [3.4L DOHC V6 (LQ1), typicalTransmissionPairing, 4-speed automatic transmission]
-
A.
usesPairsForTransmit
Indicates that an entity performs transmission by utilizing paired elements (such as wires, channels, or signals) as the medium or mechanism for sending information or energy.
-
B.
canPairRegistersFor
Indicates that two registers are compatible and allowed to be paired together for a combined or coordinated operation.
-
C.
transmitterType
Indicates the kind or category of transmitter associated with or used by an entity.
-
D.
commonPair
chosen
Indicates that two entities commonly occur together or are frequently associated as a pair in some shared context.
-
E.
featuresOnscreenPairing
Indicates that two entities appear together as an on-screen pairing within the same visual or filmed context.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07ccac9f08190b835ee7a40ecf4c2 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.