Triple
T8631834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owl |
E204420
|
entity |
| Predicate | refersToArmamentType |
P82101
|
FINISHED |
| Object | heavy cannon armament |
—
|
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: heavy cannon armament | Statement: [Owl, refersToArmamentType, heavy cannon armament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToArmamentType Context triple: [Owl, refersToArmamentType, heavy cannon armament]
-
A.
armamentCategory
chosen
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
B.
referredAircraftArmament
Indicates that one aircraft’s armament is being referenced or pointed to in relation to another entity or context.
-
C.
enemyMilitaryAsset
Indicates that one entity is a military asset belonging to or controlled by an enemy force relative to the other entity.
-
D.
weaponTypeTested
Indicates that a specific type of weapon has been subjected to a test or evaluation in the described context.
-
E.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.