Triple
T16477895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ai |
E400234
|
entity |
| Predicate | hasMilitaryTacticUsedAgainstIt |
P30685
|
FINISHED |
| Object | ambush |
—
|
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: ambush | Statement: [Ai, hasMilitaryTacticUsedAgainstIt, ambush]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryTacticUsedAgainstIt Context triple: [Ai, hasMilitaryTacticUsedAgainstIt, ambush]
-
A.
militaryForceUsed
Indicates that one entity employs or applies military power or armed force against, within, or in relation to another entity or situation.
-
B.
militaryTacticsUsed
chosen
Indicates that specific military tactics are employed or applied in the context of a particular operation, conflict, or strategic situation.
-
C.
hasArtilleryUse
Indicates that one entity employs, operates, or makes use of artillery in relation to another entity or context.
-
D.
militaryUse
Indicates the use of something (such as land, facilities, equipment, or resources) for military purposes or operations.
-
E.
wasMilitarized
Indicates that an entity underwent a process of being organized, equipped, or adapted for military use or purposes.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e0013ac8190b607d5f47d17c501 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.