Triple
T8589218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergeants School |
E203386
|
entity |
| Predicate | trainsCategory |
P83739
|
FINISHED |
| Object | non-commissioned officers |
—
|
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: non-commissioned officers | Statement: [Sergeants School, trainsCategory, non-commissioned officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsCategory Context triple: [Sergeants School, trainsCategory, non-commissioned officers]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
C.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
D.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
E.
busCategory
Indicates the classification or type of a bus within a defined categorization system.
- 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_69ca832a7f108190b4e4f5648abf4aa2 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46c5e8888190b721e791c449b0df |
completed | March 31, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cc454504448190aaad2af8b17357cd |
completed | March 31, 2026, 10:05 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:23 p.m.