Triple
T13730440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hohenfriedberger Marsch |
E329781
|
entity |
| Predicate | typicalUseBy |
P40071
|
FINISHED |
| Object | Prussian infantry units |
—
|
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: Prussian infantry units | Statement: [Hohenfriedberger Marsch, typicalUseBy, Prussian infantry units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseBy Context triple: [Hohenfriedberger Marsch, typicalUseBy, Prussian infantry units]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
partOfUse
Indicates that something functions as a component or constituent within the use or application of something else.
-
D.
primarilyUsedBy
chosen
Indicates that something is mainly or most commonly used by a particular entity or group.
-
E.
typicalSectorUse
Indicates the type of sector in which something is most commonly or characteristically used.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f92b588190be97ec4564dddd59 |
completed | April 14, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:55 p.m.