Triple
T1038929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fleet Master Chief Petty Officer |
E22425
|
entity |
| Predicate | careerField |
P24248
|
FINISHED |
| Object | enlisted leadership |
—
|
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: enlisted leadership | Statement: [Fleet Master Chief Petty Officer, careerField, enlisted leadership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerField Context triple: [Fleet Master Chief Petty Officer, careerField, enlisted leadership]
-
A.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
B.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
C.
laterCareer
Indicates that the associated information or events pertain to a later stage or phase in an entity’s professional life or career trajectory.
-
D.
careerImpact
Indicates how one entity influences or changes another entity’s professional trajectory, opportunities, or outcomes.
-
E.
partOfCareer
Indicates that one entity represents a role, position, or period that forms a component or phase within another entity’s overall career.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b97acbf4819087b92a8b29baef46 |
completed | March 1, 2026, 10:11 p.m. |
Created at: March 1, 2026, 7:41 p.m.