Triple
T11701607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hispano-Suiza 12Y |
E278138
|
entity |
| Predicate | cannonMountType |
P52740
|
FINISHED |
| Object | moteur-canon through propeller hub |
—
|
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: moteur-canon through propeller hub | Statement: [Hispano-Suiza 12Y, cannonMountType, moteur-canon through propeller hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cannonMountType Context triple: [Hispano-Suiza 12Y, cannonMountType, moteur-canon through propeller hub]
-
A.
typeOfGunMount
chosen
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
-
B.
weaponMount
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
-
C.
sightMounting
Indicates that an entity is equipped with or has a sighting device installed or mounted onto it.
-
D.
bayonetMount
Indicates that one object is equipped with or designed to accept a bayonet-style mounting connection to another object.
-
E.
mainGunModel
Indicates the specific model or type designation of the primary gun or main weapon system 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49a025881909377c81d3debf465 |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.