Triple
T6353499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Fraustadt |
E142933
|
entity |
| Predicate | capturedGunsBySwedes |
P70145
|
FINISHED |
| Object | about 30–40 artillery pieces |
—
|
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: about 30–40 artillery pieces | Statement: [Battle of Fraustadt, capturedGunsBySwedes, about 30–40 artillery pieces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capturedGunsBySwedes Context triple: [Battle of Fraustadt, capturedGunsBySwedes, about 30–40 artillery pieces]
-
A.
AustrianGunsCaptured
Indicates that guns belonging to Austrian forces were seized and taken by another party.
-
B.
SwedishCasualties
Indicates the number or extent of casualties suffered by Swedish forces or individuals in a given event or context.
-
C.
FrenchImperialGunsLost
Indicates that French imperial forces lost their artillery or guns in a particular event or context.
-
D.
capturedInWar
Indicates that one entity was taken prisoner or seized by another entity as a result of armed conflict or wartime actions.
-
E.
wasUnderSwedishRuleFrom
Indicates that one entity was governed or controlled by Sweden during a specified time period.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067dec4a88190992d57a0cc7782ad |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:31 p.m.