Triple
T31671747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian 1st Cavalry Division |
E808287
|
entity |
| Predicate | hasCavalryRegiments |
P197628
|
FINISHED |
| Object | Hungarian cavalry regiments |
—
|
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: Hungarian cavalry regiments | Statement: [Hungarian 1st Cavalry Division, hasCavalryRegiments, Hungarian cavalry regiments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCavalryRegiments Context triple: [Hungarian 1st Cavalry Division, hasCavalryRegiments, Hungarian cavalry regiments]
-
A.
hasCavalrySetting
Indicates that an entity is associated with a context, configuration, or environment specifically involving cavalry.
-
B.
hasCavalryHeritage
Indicates that an entity has a historical or traditional connection to cavalry forces or mounted military service.
-
C.
hasCavalryRole
Indicates that an entity serves in, is assigned to, or performs duties associated with a cavalry role.
-
D.
usedMilitaryCavalry
Indicates that an entity employed mounted soldiers or horse-based units as part of its military operations.
-
E.
hasArtilleryCorps
Indicates that an entity possesses, includes, or is associated with an artillery corps as part of its military forces.
- F. None of above. chosen
Provenance (4 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_69f348dbeef4819080b446a7feb6340b |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
| PDg | Predicate description generation | batch_69fe9fb88db08190a8f4af350633330e |
completed | May 9, 2026, 2:45 a.m. |
Created at: April 30, 2026, 11:01 p.m.