Triple
T32775153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kershaw’s Brigade marker |
E838178
|
entity |
| Predicate | hasMilitarySide |
P22805
|
FINISHED |
| Object | Confederate |
—
|
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: Confederate | Statement: [Kershaw’s Brigade marker, hasMilitarySide, Confederate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitarySide Context triple: [Kershaw’s Brigade marker, hasMilitarySide, Confederate]
-
A.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
B.
hasMilitaryText
Indicates that an entity possesses or is associated with a text whose content is military in nature (e.g., about armed forces, warfare, or defense).
-
C.
hasMilitaryAssociation
chosen
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
-
D.
usesMilitaryUnit
Indicates that one entity employs, deploys, or otherwise makes operational use of a specific military unit.
-
E.
hasMilitaryClass
Indicates that an entity belongs to, is assigned to, or is categorized under a specific military class or classification.
- 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_69f3493a824c8190938489ba69041d08 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:13 a.m.