Triple
T31699101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Action at Belmont |
E809002
|
entity |
| Predicate | confederateCasualtiesKilledWoundedMissing |
P34511
|
FINISHED |
| Object | approximately 641 |
—
|
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 641 | Statement: [Action at Belmont, confederateCasualtiesKilledWoundedMissing, approximately 641]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: confederateCasualtiesKilledWoundedMissing Context triple: [Action at Belmont, confederateCasualtiesKilledWoundedMissing, approximately 641]
-
A.
confederateCasualtiesAndLosses
chosen
Indicates the number or extent of casualties and material losses suffered by Confederate forces in a conflict or engagement.
-
B.
confederatePrisonersTaken
Indicates that one party has captured and taken prisoners who are affiliated with or fighting for the Confederate side.
-
C.
UScasualties
Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, or situation.
-
D.
hasConfederateBurialCount
Indicates the number of Confederate burials associated with a given entity or site.
-
E.
ConfederateOfficerKilled
Indicates that an individual serving as a Confederate officer was killed.
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: April 30, 2026, 11:11 p.m.