Triple
T16302882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wankel rotary engine |
E395833
|
entity |
| Predicate | combustionChambersPerRotor |
P80789
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [Wankel rotary engine, combustionChambersPerRotor, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combustionChambersPerRotor Context triple: [Wankel rotary engine, combustionChambersPerRotor, three]
-
A.
combustionChamberCount
chosen
Indicates the number of combustion chambers associated with an engine or combustion system.
-
B.
combustionChamber
Indicates that one entity functions as the combustion chamber in which another entity’s fuel–air mixture is burned to produce energy or propulsion.
-
C.
numberOfBladesMainRotor
Indicates the quantity of blades present on the main rotor in the relationship or system being described.
-
D.
propellerBladesPerPropeller
Indicates the number of blades associated with each individual propeller.
-
E.
numberOfEngines
Indicates the quantity of engines associated with or used by an entity.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e3404288190a7106d62c15c3193 |
completed | April 17, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.