Triple
T7444804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five College Certificate in Buddhist Studies |
E171849
|
entity |
| Predicate | includesCoursesFrom |
P62594
|
FINISHED |
| Object | multiple departments |
—
|
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: multiple departments | Statement: [Five College Certificate in Buddhist Studies, includesCoursesFrom, multiple departments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCoursesFrom Context triple: [Five College Certificate in Buddhist Studies, includesCoursesFrom, multiple departments]
-
A.
curriculumIncluded
chosen
Indicates that a particular subject, topic, or component is part of a defined curriculum or course of study.
-
B.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
C.
usesCourse
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
D.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
E.
isLinksCourse
Indicates that one course is linked or associated with another course in a meaningful way (such as being related, connected, or part of the same learning path).
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f37054388190a6cb4c0db2ca6014 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:14 p.m.