Triple
T482193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane C. Ginsburg |
E9192
|
entity |
| Predicate | hasTaughtCourse |
P3295
|
FINISHED |
| Object | copyright 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: copyright law | Statement: [Jane C. Ginsburg, hasTaughtCourse, copyright law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaughtCourse Context triple: [Jane C. Ginsburg, hasTaughtCourse, copyright law]
-
A.
gradesTaught
Indicates the set of grade levels that a teacher or educational entity is responsible for teaching.
-
B.
hasTeachingRole
chosen
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
-
C.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
D.
hasTeachingAuthority
Indicates that one entity possesses the recognized power or right to teach, instruct, or provide formal education to another entity or within a specific context.
-
E.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f05a7f6c819082b4a5a3e69468a6 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf321288190b5d560f75782c2cb |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.