Triple
T584782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Leuthen |
E15134
|
entity |
| Predicate | casualtiesPrussia |
P1399
|
FINISHED |
| Object | several thousand killed and wounded |
—
|
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: several thousand killed and wounded | Statement: [Battle of Leuthen, casualtiesPrussia, several thousand killed and wounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesPrussia Context triple: [Battle of Leuthen, casualtiesPrussia, several thousand killed and wounded]
-
A.
casualtiesGermanWounded
Indicates that the relationship specifies the number of German individuals who were wounded (but not killed) as casualties in a particular event or context.
-
B.
numberOfGermanVictims
Indicates the quantity of victims who are identified as German in the context of the described event or situation.
-
C.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
D.
casualties
chosen
Indicates that an event, action, or situation resulted in people being killed or injured.
-
E.
casualtiesAtStalingrad
Indicates that an entity experienced casualties (killed, wounded, or missing) in connection with the Battle of Stalingrad.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9874c88190bd1e08d4689ea124 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.