Triple
T2109274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voroshilov General Staff Academy |
E42466
|
entity |
| Predicate | rankOfTypicalStudents |
P34817
|
FINISHED |
| Object | colonel |
—
|
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: colonel | Statement: [Voroshilov General Staff Academy, rankOfTypicalStudents, colonel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankOfTypicalStudents Context triple: [Voroshilov General Staff Academy, rankOfTypicalStudents, colonel]
-
A.
gradeRank
Indicates the relative academic standing or position of an entity within a graded or ranked group based on performance or scores.
-
B.
educationRanking
Indicates the relative position or level assigned to an entity based on the quality or performance of its educational attributes or outcomes.
-
C.
rankGrade
Indicates the grade or level assigned to an entity within a ranking or evaluation system.
-
D.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
E.
grades
Indicates that one entity evaluates and assigns a score or level of performance to another entity.
- F. None of above. chosen
Provenance (4 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae1bacc8190beffc9d0470e9190 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:43 p.m.