Triple
T9828468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Modern Languages and Literatures |
E238719
|
entity |
| Predicate | typicalCourses |
P11940
|
FINISHED |
| Object | language acquisition |
—
|
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: language acquisition | Statement: [Department of Modern Languages and Literatures, typicalCourses, language acquisition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCourses Context triple: [Department of Modern Languages and Literatures, typicalCourses, language acquisition]
-
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.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
C.
notableCourseType
Indicates that a course has a particular notable or distinguished type or classification (e.g., flagship, honors, or otherwise specially recognized).
-
D.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
E.
notableCourse
Indicates that a course is particularly significant, distinguished, or noteworthy in relation to an entity (such as a person or institution).
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3268fcc8190b7a028f224512e5f |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.