Triple
T6353497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Fraustadt |
E142933
|
entity |
| Predicate | prisonersTakenBySwedes |
P6764
|
FINISHED |
| Object | about 7,000–8,000 prisoners |
—
|
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 7,000–8,000 prisoners | Statement: [Battle of Fraustadt, prisonersTakenBySwedes, about 7,000–8,000 prisoners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prisonersTakenBySwedes Context triple: [Battle of Fraustadt, prisonersTakenBySwedes, about 7,000–8,000 prisoners]
-
A.
carriedPrisonersFrom
Indicates that an entity transported prisoners away from a specified origin location or source.
-
B.
prisonersOfWar
chosen
Indicates a relationship where certain individuals are held in custody by an enemy during an armed conflict as prisoners of war.
-
C.
detainedPrisonersFrom
Indicates that an authority is holding prisoners who originate from or are associated with a specified place or source.
-
D.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
-
E.
AustrianGunsCaptured
Indicates that guns belonging to Austrian forces were seized and taken by another party.
- 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_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. |
Created at: March 22, 2026, 4:31 p.m.