Triple
T33093839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Command Sergeant Major (USA) |
E846854
|
entity |
| Predicate | typical unit level |
P11280
|
FINISHED |
| Object | battalion |
—
|
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: battalion | Statement: [Command Sergeant Major (USA), typical unit level, battalion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typical unit level Context triple: [Command Sergeant Major (USA), typical unit level, battalion]
-
A.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
-
B.
typicalLowestLevel
Indicates that something represents the most basic or minimal level that is commonly or normally found within a given context.
-
C.
typicalCommandLevel
chosen
Indicates the usual or standard level of authority or access at which a command is intended to be executed.
-
D.
basicLevelUnits
Indicates that the related entities are connected through a shared basic-level unit or category that groups them at a fundamental level of classification.
-
E.
typicalHighestLevel
Indicates the usual or most common maximum level or degree that something typically reaches within a given context.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:26 a.m.