Triple
T17160453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Škoda Octavia (China) |
E416461
|
entity |
| Predicate | numberOfCylindersOption |
P8251
|
FINISHED |
| Object | 4-cylinder engines |
—
|
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-cylinder engines | Statement: [Škoda Octavia (China), numberOfCylindersOption, 4-cylinder engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCylindersOption Context triple: [Škoda Octavia (China), numberOfCylindersOption, 4-cylinder engines]
-
A.
numberOfCylinders
chosen
Indicates the count of engine cylinders associated with an entity.
-
B.
cylinderHeads
Indicates a relationship where one entity serves as a cylinder head (or set of cylinder heads) for another, typically as a component in an engine or mechanical assembly.
-
C.
valvesPerCylinder
Indicates the number of valves associated with each individual cylinder in an engine.
-
D.
numberOfCarburetors
Indicates the quantity of carburetors associated with a given entity.
-
E.
cylinderHeadBrand
Indicates the brand or manufacturer associated with a cylinder head.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f911114481909c865b2e2d3b3a2b |
completed | April 18, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.