Triple
T19338350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Navy enlisted community |
E483680
|
entity |
| Predicate | hasCareerPath |
P14530
|
FINISHED |
| Object | technical specialist |
—
|
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: technical specialist | Statement: [United States Navy enlisted community, hasCareerPath, technical specialist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCareerPath Context triple: [United States Navy enlisted community, hasCareerPath, technical specialist]
-
A.
hasCareerTrack
chosen
Indicates that an entity is associated with or follows a particular career path or professional progression.
-
B.
acceptsCareerPath
Indicates that one entity approves or agrees to follow a proposed career path associated with another entity.
-
C.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
D.
careerPath
Indicates the progression or sequence of roles, positions, or occupations that an individual follows over time in their professional life.
-
E.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6185538d48190ae4fa3ac0b0ca182 |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.