Triple
T24322605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia and Prussia |
E613008
|
entity |
| Predicate | hadArmiesThat |
P155551
|
FINISHED |
| Object | fought jointly in Central Europe against French forces |
—
|
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: fought jointly in Central Europe against French forces | Statement: [Russia and Prussia, hadArmiesThat, fought jointly in Central Europe against French forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadArmiesThat Context triple: [Russia and Prussia, hadArmiesThat, fought jointly in Central Europe against French forces]
-
A.
servedArmy
Indicates that an entity has performed military service in, or been a member of, a particular army.
-
B.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
C.
foughtAs
Indicates that an entity participated in a conflict or war in the capacity, role, or identity specified by another entity.
-
D.
hasConqueringEmpire
Indicates that one entity is an empire that has militarily defeated and taken control over another entity.
-
E.
hasMilitarySignificanceSince
Indicates that something has held military importance or strategic value starting from a specified point in time.
- 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_69e2d7da491c8190b6e6218af50923db |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292ad4cc881908794b501cf70b7a1 |
completed | April 29, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f1c45f45888190a9ccc225906c34bd |
completed | April 29, 2026, 8:42 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 1:52 a.m.