Triple
T9521506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vickers 6-Ton tank |
E229653
|
entity |
| Predicate | armamentVariant |
P28675
|
FINISHED |
| Object | twin machine-gun turrets |
—
|
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: twin machine-gun turrets | Statement: [Vickers 6-Ton tank, armamentVariant, twin machine-gun turrets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentVariant Context triple: [Vickers 6-Ton tank, armamentVariant, twin machine-gun turrets]
-
A.
armedVariants
chosen
Indicates that one entity is a version or model of another that is equipped with weapons or enhanced armaments.
-
B.
isMilitaryVariantOf
Indicates that one entity is a military-specific version or adaptation of another, typically civilian or general-purpose, entity.
-
C.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
D.
armamentFlexible
Indicates that an entity’s armament or weapon configuration can be adjusted, reconfigured, or adapted to different setups or roles.
-
E.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9884dd5c8190b69c178cb2ac75c2 |
completed | April 1, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cca56a3d088190bdc16670678fb6c6 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:59 p.m.