Triple
T30997980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dankook University (Cheonan campus) |
E789855
|
entity |
| Predicate | offersCoursesInLanguage |
P29959
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Dankook University (Cheonan campus), offersCoursesInLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersCoursesInLanguage Context triple: [Dankook University (Cheonan campus), offersCoursesInLanguage, English]
-
A.
offersProgramsInLanguage
chosen
Indicates that an entity provides or conducts its programs using a specified language.
-
B.
offersCourseType
Indicates that an entity provides or makes available a course of a specified type.
-
C.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
D.
offersEducationIn
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
E.
offersCurriculum
Indicates that one entity provides or makes available a specific curriculum to another entity.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
Created at: April 29, 2026, 8:56 p.m.