Triple
T21131939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M11/39 medium tank |
E520708
|
entity |
| Predicate | hasTurretArmament |
P126954
|
FINISHED |
| Object | twin machine 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: twin machine guns | Statement: [M11/39 medium tank, hasTurretArmament, twin machine guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurretArmament Context triple: [M11/39 medium tank, hasTurretArmament, twin machine guns]
-
A.
hasTurrets
Indicates that an entity is equipped with or possesses one or more turrets.
-
B.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
C.
hasTurretType
Indicates that one entity is equipped with or characterized by a specific type of turret.
-
D.
tertiaryArmament
chosen
Indicates the relationship where an entity possesses or is equipped with a third-level (tertiary) weapon or armament beyond its primary and secondary armaments.
-
E.
turretCount
Indicates the number of turrets associated with or mounted on a given 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235668e081909bd810016ba2dd8e |
completed | April 21, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:56 p.m.