Triple
T28010992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunan Medical University |
E707416
|
entity |
| Predicate | hadEducationalLevel |
P27439
|
FINISHED |
| Object | postgraduate |
—
|
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: postgraduate | Statement: [Hunan Medical University, hadEducationalLevel, postgraduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadEducationalLevel Context triple: [Hunan Medical University, hadEducationalLevel, postgraduate]
-
A.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
B.
educationStatus
chosen
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
C.
educationLevelCharacteristic
Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
-
D.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
-
E.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
- 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_69ef96ba350c81908230d0b501b974c4 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63fd79e4c8190af9263b679e5ff07 |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 8:03 p.m.