Triple
T19824151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese battleship Tosa |
E476274
|
entity |
| Predicate | designedAntiAircraftArmament |
P118958
|
FINISHED |
| Object | 4 × 8 cm (3 in) AA guns |
—
|
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 × 8 cm (3 in) AA guns | Statement: [Japanese battleship Tosa, designedAntiAircraftArmament, 4 × 8 cm (3 in) AA guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedAntiAircraftArmament Context triple: [Japanese battleship Tosa, designedAntiAircraftArmament, 4 × 8 cm (3 in) AA guns]
-
A.
aircraftDefensiveArmament
Indicates that an aircraft is equipped with weapons or systems specifically intended for its own defense against attacks.
-
B.
airDefenseArmament
chosen
Indicates the weapons or systems specifically equipped on an entity for defending against aerial threats such as aircraft or missiles.
-
C.
referredAircraftArmament
Indicates that one aircraft’s armament is being referenced or pointed to in relation to another entity or context.
-
D.
airDefenseSystemComponent
Indicates that one entity is a component or subsystem of an air defense system associated with another entity.
-
E.
airDefenseSystem
Indicates a defensive military system designed to detect, track, and engage airborne threats such as aircraft or missiles.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e655017c188190ae9e17ae6b0eee05 |
completed | April 20, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.