Triple
T649577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fighter Ground attack Reconnaissance Mark 4 |
E11315
|
entity |
| Predicate | typicalArmament |
P7745
|
FINISHED |
| Object | air-to-air missiles |
—
|
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: air-to-air missiles | Statement: [Fighter Ground attack Reconnaissance Mark 4, typicalArmament, air-to-air missiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalArmament Context triple: [Fighter Ground attack Reconnaissance Mark 4, typicalArmament, air-to-air missiles]
-
A.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
B.
typicalWeapon
chosen
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
C.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
D.
secondaryArmament
Indicates that one entity serves as a secondary or auxiliary weapon system associated with another primary platform or armament.
-
E.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.