Triple
T2558317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army of Flanders |
E56780
|
entity |
| Predicate | usedMilitaryUnitType |
P15598
|
FINISHED |
| Object | tercio |
—
|
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: tercio | Statement: [Army of Flanders, usedMilitaryUnitType, tercio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedMilitaryUnitType Context triple: [Army of Flanders, usedMilitaryUnitType, tercio]
-
A.
militaryUse
Indicates the use of something (such as land, facilities, equipment, or resources) for military purposes or operations.
-
B.
hasMilitaryDesignation
Indicates that an entity is assigned a specific military-related code, title, or classification.
-
C.
militaryFunction
Indicates a relationship where an entity serves a specific role, duty, or operational purpose within a military context.
-
D.
usedWarfareType
Indicates the specific type or method of warfare that an entity employed in a conflict or military context.
-
E.
usedMilitaryFormation
chosen
Indicates that an entity employed a specific military formation or tactical arrangement of forces in a military context.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.