Triple
T23720411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bitwa pod Wschową |
E586127
|
entity |
| Predicate | liczebnośćArmiiSaskoRosyjskiej |
P6153
|
FINISHED |
| Object | około 20 000–22 000 żołnierzy |
—
|
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: około 20 000–22 000 żołnierzy | Statement: [Bitwa pod Wschową, liczebnośćArmiiSaskoRosyjskiej, około 20 000–22 000 żołnierzy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liczebnośćArmiiSaskoRosyjskiej Context triple: [Bitwa pod Wschową, liczebnośćArmiiSaskoRosyjskiej, około 20 000–22 000 żołnierzy]
-
A.
numberOfRegimentsInvolved
Indicates the total count of regiments that participated in or were involved in a specified event or action.
-
B.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
C.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
D.
commandingForceSize
Indicates the size or magnitude of the military or organizational force that is exercising command or control in a given context.
-
E.
militaryCasualtiesSide
Indicates the side or party in a conflict to which the recorded military casualties belong.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b910759c8190be189db3e86d7258 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7 p.m.