Triple
T729471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Rossbach |
E14799
|
entity |
| Predicate | FrenchImperialCasualties |
P14905
|
FINISHED |
| Object | around 7,000–10,000 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: around 7,000–10,000 killed and wounded | Statement: [Battle of Rossbach, FrenchImperialCasualties, around 7,000–10,000 killed and wounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchImperialCasualties Context triple: [Battle of Rossbach, FrenchImperialCasualties, around 7,000–10,000 killed and wounded]
-
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.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
C.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
D.
NATOcasualtiesMilitaryKilled
Indicates that members of NATO military forces were killed as casualties.
-
E.
countryOfDefeatedSide
Indicates the country to which the losing or defeated side in a conflict, competition, or confrontation belongs.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f9b7608190bf97c8418a26e632 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.