Triple
T729472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Rossbach |
E14799
|
entity |
| Predicate | FrenchImperialPrisoners |
P6764
|
FINISHED |
| Object | around 5,000–7,000 captured |
—
|
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 5,000–7,000 captured | Statement: [Battle of Rossbach, FrenchImperialPrisoners, around 5,000–7,000 captured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchImperialPrisoners Context triple: [Battle of Rossbach, FrenchImperialPrisoners, around 5,000–7,000 captured]
-
A.
prisonersOfWar
chosen
Indicates a relationship where certain individuals are held in custody by an enemy during an armed conflict as prisoners of war.
-
B.
carriedPrisonersFrom
Indicates that an entity transported prisoners away from a specified origin location or source.
-
C.
estimatedNumberOfSurvivorsAtLiberation
Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
-
D.
wasImprisonedIn
Indicates that an entity was held in confinement or incarcerated at a particular place or facility.
-
E.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
- 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.