Triple
T36992878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuhada of Pakistan Armed Forces |
E915151
|
entity |
| Predicate | includeCasualtiesFrom |
—
|
GENERATED |
| Object | Indo-Pakistani wars |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includeCasualtiesFrom Context triple: [Shuhada of Pakistan Armed Forces, includeCasualtiesFrom, Indo-Pakistani wars]
-
A.
casualtiesIncluded
chosen
Indicates that the referenced count or report of casualties explicitly includes the specified individuals or groups.
-
B.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
-
C.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
D.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
E.
secondaryCasualtiesFrom
Indicates that an entity experiences indirect or collateral harm as a consequence of another primary event or source.
- F. None of above.
Provenance (1 batch)
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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:14 p.m.