Triple
T29642905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval Ordnance Training Center |
E755910
|
entity |
| Predicate | subjectOfTraining |
P153131
|
FINISHED |
| Object | handling of naval weapons |
—
|
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: handling of naval weapons | Statement: [Naval Ordnance Training Center, subjectOfTraining, handling of naval weapons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOfTraining Context triple: [Naval Ordnance Training Center, subjectOfTraining, handling of naval weapons]
-
A.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
B.
trainingIn
chosen
Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
-
C.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
D.
trainedAccordingTo
Indicates that an entity has been trained or instructed in alignment with a specified method, standard, guideline, or curriculum.
-
E.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 28, 2026, 6:48 p.m.