Triple
T461041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juris Doctor |
E7336
|
entity |
| Predicate | typicalCurriculumComponent |
P11940
|
FINISHED |
| Object | contracts |
—
|
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: contracts | Statement: [Juris Doctor, typicalCurriculumComponent, contracts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCurriculumComponent Context triple: [Juris Doctor, typicalCurriculumComponent, contracts]
-
A.
typicalCourse
chosen
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
-
B.
courseStructure
Indicates how a course is organized into its constituent parts, such as modules, units, lessons, and their sequencing or hierarchy.
-
C.
usesCurriculum
Indicates that one entity adopts or applies a particular curriculum as the basis for its instruction, training, or educational activities.
-
D.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
E.
educationalActivity
Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.