Triple
T16164705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Tupelo |
E392272
|
entity |
| Predicate | UnionCasualtiesKilledAndWounded |
P121650
|
FINISHED |
| Object | approximately 650 |
—
|
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: approximately 650 | Statement: [Battle of Tupelo, UnionCasualtiesKilledAndWounded, approximately 650]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UnionCasualtiesKilledAndWounded Context triple: [Battle of Tupelo, UnionCasualtiesKilledAndWounded, approximately 650]
-
A.
englishCasualtiesKilledAndWounded
Indicates the number of English individuals who were either killed or wounded as a result of a particular event or conflict.
-
B.
UnionKilledAndWounded
Indicates that members of the Union side in a conflict caused deaths and injuries to others.
-
C.
casualtiesUnion
Indicates a relationship where multiple casualty figures or reports are combined into a single aggregated total.
-
D.
militaryCasualtiesSide
Indicates the side or party in a conflict to which the recorded military casualties belong.
-
E.
casualtiesKilledAndMortallyWounded
Indicates that the relationship records the number of individuals who were killed outright or died later from mortal wounds.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e622ae481909f3cf25b38886d3a |
completed | April 17, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e18445155481909892b8aaa23cc159 |
completed | April 17, 2026, 12:52 a.m. |
Created at: April 10, 2026, 5:02 a.m.