Triple
T32356633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Drewry’s Bluff |
E826748
|
entity |
| Predicate | casualtiesConfederateKilledAndWounded |
P62746
|
FINISHED |
| Object | approximately 15 |
—
|
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 15 | Statement: [Battle of Drewry’s Bluff, casualtiesConfederateKilledAndWounded, approximately 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: casualtiesConfederateKilledAndWounded Context triple: [Battle of Drewry’s Bluff, casualtiesConfederateKilledAndWounded, approximately 15]
-
A.
confederateCasualtiesAndLosses
Indicates the number or extent of casualties and material losses suffered by Confederate forces in a conflict or engagement.
-
B.
casualtiesKilledAndMortallyWounded
chosen
Indicates that the relationship records the number of individuals who were killed outright or died later from mortal wounds.
-
C.
ConfederateOfficerKilled
Indicates that an individual serving as a Confederate officer was killed.
-
D.
UnionKilledAndWounded
Indicates that members of the Union side in a conflict caused deaths and injuries to others.
-
E.
casualtiesTexianKilled
Indicates that the relationship specifies the number of Texian individuals who were killed as casualties in a particular event or conflict.
- 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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 12:49 a.m.