Triple
T6750102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of Laws (Dr. iur.) |
E154320
|
entity |
| Predicate | academicRankPreparationFor |
P6
|
FINISHED |
| Object | university-level teaching in law |
—
|
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: university-level teaching in law | Statement: [Doctor of Laws (Dr. iur.), academicRankPreparationFor, university-level teaching in law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicRankPreparationFor Context triple: [Doctor of Laws (Dr. iur.), academicRankPreparationFor, university-level teaching in law]
-
A.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
B.
academicDegree
chosen
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
D.
hasAcademicRank
Indicates that an entity holds a specific academic rank or title within an educational or research institution.
-
E.
positionOnEducation
Indicates a stance, opinion, or policy view that an entity holds regarding education-related issues.
- 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.