Triple
T22502311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Klissow |
E556303
|
entity |
| Predicate | SaxonPolishCasualties |
P23378
|
FINISHED |
| Object | several thousand 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: several thousand killed and wounded | Statement: [Battle of Klissow, SaxonPolishCasualties, several thousand killed and wounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SaxonPolishCasualties Context triple: [Battle of Klissow, SaxonPolishCasualties, several thousand killed and wounded]
-
A.
PolishCasualties
chosen
Indicates the number or extent of casualties suffered by Polish forces or population in a given conflict or event.
-
B.
PolishUnit
Indicates that a unit is associated with Poland, typically by nationality, origin, or affiliation.
-
C.
militaryCasualtiesSide
Indicates the side or party in a conflict to which the recorded military casualties belong.
-
D.
polishForcesRole
Indicates that an entity serves in, is associated with, or has a specific role within the Polish armed forces.
-
E.
rolaWZimnejWojnie
Indicates a role or involvement that one entity had in the context of the Cold War.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb6b47481909855fe93e95da7e7 |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.