Triple
T24115229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navy Nurse Corps officers |
E597490
|
entity |
| Predicate | mayHaveEducation |
P122287
|
FINISHED |
| Object | Master of Science in Nursing |
—
|
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: Master of Science in Nursing | Statement: [Navy Nurse Corps officers, mayHaveEducation, Master of Science in Nursing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveEducation Context triple: [Navy Nurse Corps officers, mayHaveEducation, Master of Science in Nursing]
-
A.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
-
B.
hasEducationalAchievement
chosen
Indicates that an entity has attained a specific level, degree, or form of formal educational accomplishment.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
hasEducationalStatus
Indicates that an entity possesses a particular level, state, or condition of formal education or academic attainment.
- 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dedebb748190b8fe295d6dc0a9a7 |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:04 p.m.