Triple
T26681424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Training Ship Kennedy |
E672621
|
entity |
| Predicate | safetyTraining |
P81165
|
FINISHED |
| Object | emergency response exercises |
—
|
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: emergency response exercises | Statement: [Training Ship Kennedy, safetyTraining, emergency response exercises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyTraining Context triple: [Training Ship Kennedy, safetyTraining, emergency response exercises]
-
A.
safetyPrograms
Indicates that there are organized measures, policies, or initiatives implemented to protect people or assets from harm or risk.
-
B.
safetyLesson
chosen
Indicates that an entity conducts, provides, or is involved in a lesson or instruction focused on safety practices or precautions.
-
C.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
D.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
E.
safetyCategory
Indicates the classification of something according to its level or type of safety.
- 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_69eecda13424819092b17942c4edf722 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 3:20 a.m.