Triple
T35003480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salyut 3 |
E1009746
|
entity |
| Predicate | hadOnboardWeapon |
P165494
|
FINISHED |
| Object | 23 mm autocannon |
—
|
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: 23 mm autocannon | Statement: [Salyut 3, hadOnboardWeapon, 23 mm autocannon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadOnboardWeapon Context triple: [Salyut 3, hadOnboardWeapon, 23 mm autocannon]
-
A.
hasHumanBuiltWeapon
Indicates that an entity possesses, controls, or is equipped with a weapon that has been constructed or manufactured by humans.
-
B.
weaponryCarried
chosen
Indicates that one entity is carrying or equipped with a weapon or set of weapons in relation to another entity or context.
-
C.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
D.
hasKillerWeapon
Indicates that a particular weapon was used by an entity to commit a killing.
-
E.
carriedConcealedWeapon
Indicates that an entity possessed and transported a weapon in a hidden or non-visible manner.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7858aa5508190a07dde993b3356fc |
completed | May 3, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.