Triple
T21591930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Infantry Basic Officer Leader Course |
E532801
|
entity |
| Predicate | rankRangeOfStudents |
P16498
|
FINISHED |
| Object | second lieutenant to first lieutenant |
—
|
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: second lieutenant to first lieutenant | Statement: [Infantry Basic Officer Leader Course, rankRangeOfStudents, second lieutenant to first lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankRangeOfStudents Context triple: [Infantry Basic Officer Leader Course, rankRangeOfStudents, second lieutenant to first lieutenant]
-
A.
rankOfTypicalStudents
Indicates the usual or most common rank or standing that students hold within a given group or context.
-
B.
gradeRank
Indicates the relative academic standing or position of an entity within a graded or ranked group based on performance or scores.
-
C.
gradeRange
Indicates the span of grades or scores that an item, performance, or entity falls within.
-
D.
gradeWithinClass
Indicates that an entity’s grade or performance level is evaluated and assigned relative to other members within the same class or group.
-
E.
rankRange
chosen
Indicates that an entity’s rank falls within a specified minimum and maximum range.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadeb56c8190bce79efadf3c644d |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.