Triple
T6750125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of Laws (Dr. iur.) |
E154320
|
entity |
| Predicate | positionInEducationSystem |
P27439
|
FINISHED |
| Object | third cycle of higher education |
—
|
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: third cycle of higher education | Statement: [Doctor of Laws (Dr. iur.), positionInEducationSystem, third cycle of higher education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInEducationSystem Context triple: [Doctor of Laws (Dr. iur.), positionInEducationSystem, third cycle of higher education]
-
A.
positionOnEducation
Indicates a stance, opinion, or policy view that an entity holds regarding education-related issues.
-
B.
educationStatus
chosen
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
educationIndicator
Indicates that there is a measure or metric reflecting some aspect of educational status, performance, or outcomes associated with the entities.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.