Triple
T1232963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polish II Corps |
E26483
|
entity |
| Predicate | warDead |
P1785
|
FINISHED |
| Object | several thousand killed in action in the Italian Campaign |
—
|
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 in action in the Italian Campaign | Statement: [Polish II Corps, warDead, several thousand killed in action in the Italian Campaign]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warDead Context triple: [Polish II Corps, warDead, several thousand killed in action in the Italian Campaign]
-
A.
worldWar
Indicates a large-scale armed conflict involving multiple nations across different regions of the world, typically encompassing numerous battles, alliances, and theaters of war.
-
B.
warCry
Indicates a relationship where an entity utters or performs a loud, rallying shout or chant intended to inspire allies or intimidate opponents, typically in a conflict or competitive context.
-
C.
majorWar
Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
-
D.
warDamage
Indicates damage that was caused as a direct consequence of war or armed conflict.
-
E.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5b40208190b115a6a344402caf |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.