Triple
T6541061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Lützen (1813) |
E168287
|
entity |
| Predicate | casualtiesAndLossesFrench |
P14905
|
FINISHED |
| Object | tens of thousands killed and wounded (approx. 18000–20000) |
—
|
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: tens of thousands killed and wounded (approx. 18000–20000) | Statement: [Battle of Lützen (1813), casualtiesAndLossesFrench, tens of thousands killed and wounded (approx. 18000–20000)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesAndLossesFrench Context triple: [Battle of Lützen (1813), casualtiesAndLossesFrench, tens of thousands killed and wounded (approx. 18000–20000)]
-
A.
FrenchCasualties
chosen
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
-
B.
casualtiesFrancoBavarian
Indicates that there were casualties suffered by the Franco-Bavarian side in a particular conflict or event.
-
C.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
D.
frenchTroopsEvacuated
Indicates that French military forces withdrew or were removed from a particular location or situation.
-
E.
casualtiesUnion
Indicates a relationship where multiple casualty figures or reports are combined into a single aggregated total.
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:50 p.m.