Triple
T6802908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bumin Campus |
E156229
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Dong-A University |
E29057
|
NE 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: Dong-A University | Statement: [Bumin Campus, partOf, Dong-A University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dong-A University Context triple: [Bumin Campus, partOf, Dong-A University]
-
A.
Dong-A University
chosen
Dong-A University is a major private research university in Busan, South Korea, known for its comprehensive academic programs and multiple urban campuses.
-
B.
Dongguk University
Dongguk University is a prominent private university in South Korea known for its Buddhist foundation and strong programs in the humanities, arts, and social sciences.
-
C.
Sungkyul University
Sungkyul University is a South Korean higher education institution known for producing alumni such as actor Wi Ha-joon.
-
D.
Chosun University
Chosun University is a major private research university in South Korea known for its comprehensive academic programs and regional influence.
-
E.
Daegu University
Daegu University is a South Korean higher education institution known for its comprehensive academic programs and strong emphasis on social welfare and special education.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2e714d4819084c8109c4de7de72 |
completed | March 27, 2026, 6:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7daf7529c8190b70ac11fb4c9ba32 |
completed | March 28, 2026, 1:43 p.m. |
Created at: March 27, 2026, 2:16 p.m.