Triple
T36849694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Pharmaceutics |
E910641
|
entity |
| Predicate | teachesCourseIn |
P48837
|
FINISHED |
| Object | dosage form design |
—
|
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: dosage form design | Statement: [Department of Pharmaceutics, teachesCourseIn, dosage form design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesCourseIn Context triple: [Department of Pharmaceutics, teachesCourseIn, dosage form design]
-
A.
alsoTeachesIn
Indicates that an individual who teaches in one context or institution additionally teaches in another context or institution.
-
B.
areTaughtIn
chosen
Indicates that certain subjects, courses, or topics are instructed or delivered within specific locations, classes, or educational settings.
-
C.
isTaughtTo
Indicates that some knowledge, skill, or subject is being instructed or conveyed by a teacher or source to a learner or recipient.
-
D.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
-
E.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
- 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_69f76e8033d48190a59274f86f13be48 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:13 p.m.