Triple
T5195437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 83rd Pennsylvania Infantry |
E117258
|
entity |
| Predicate | killedOrMortallyWounded |
P62389
|
FINISHED |
| Object | about 282 officers and men |
—
|
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 282 officers and men | Statement: [83rd Pennsylvania Infantry, killedOrMortallyWounded, about 282 officers and men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killedOrMortallyWounded Context triple: [83rd Pennsylvania Infantry, killedOrMortallyWounded, about 282 officers and men]
-
A.
killedBy
Indicates that one entity caused the death of another entity.
-
B.
fatalInjury
Indicates that an entity causes or sustains an injury that directly results in death.
-
C.
wasWoundedIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
-
D.
killedDuring
Indicates that one entity caused the death of another entity in the course of, or as part of, a specified event or time period.
-
E.
crewFatality
Indicates that one or more members of a crew have died as a result of the related event or situation.
- F. None of above. chosen
Provenance (4 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7adb034c819086bf8a85fbf158f4 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77b9a67c8190819612257ea746b4 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7ad9bdd88190ae8aa6f4aba695a7 |
completed | March 20, 2026, 4:50 p.m. |
Created at: March 20, 2026, 1:46 p.m.