Triple
T531692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunpowder Empires |
E12235
|
entity |
| Predicate | hasMilitaryFeature |
P7256
|
FINISHED |
| Object | standing army |
—
|
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: standing army | Statement: [Gunpowder Empires, hasMilitaryFeature, standing army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryFeature Context triple: [Gunpowder Empires, hasMilitaryFeature, standing army]
-
A.
militaryCharacteristic
chosen
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
B.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
C.
hasMilitaryBase
Indicates that one entity possesses, hosts, or contains a military base associated with or located on another entity.
-
D.
militaryFunction
Indicates a relationship where an entity serves a specific role, duty, or operational purpose within a military context.
-
E.
militaryMeasure
Indicates a relationship where an entity undertakes, imposes, or is subject to a specific military-related action, policy, or operational measure.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b257108190a537dffbb9d621b5 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.