Triple
T20796156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daegu |
E511913
|
entity |
| Predicate | majorUniversity |
P315
|
FINISHED |
| Object | Keimyung University |
—
|
NE NERFINISHED |
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: Keimyung University | Statement: [Daegu, majorUniversity, Keimyung University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keimyung University Context triple: [Daegu, majorUniversity, Keimyung University]
-
A.
Keimyung University
chosen
Keimyung University is a private Christian university in Daegu, South Korea, known for its international programs and picturesque campus.
-
B.
Kyungsung University
Kyungsung University is a private higher education institution located in Busan, South Korea, known for its programs in humanities, social sciences, arts, and media.
-
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.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2ad6f0481909e0bab7119f10f9c |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:39 p.m.