Triple
T1359106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dong-A University |
E29057
|
entity |
| Predicate | hasCampus |
P116
|
FINISHED |
| Object | Seunghak Campus |
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: Seunghak Campus | Statement: [Dong-A University, hasCampus, Seunghak Campus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seunghak Campus Context triple: [Dong-A University, hasCampus, Seunghak Campus]
-
A.
Hanbat National University
Hanbat National University is a public university in South Korea known for its strong engineering, technology, and design programs.
-
B.
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.
-
C.
University of Ulsan
The University of Ulsan is a major private research university in Ulsan, South Korea, known for its strong engineering and industrial cooperation programs.
-
D.
Keimyung University
Keimyung University is a private Christian university in Daegu, South Korea, known for its international programs and picturesque campus.
-
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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c290db288190910fcfa17e902663 |
completed | March 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad293ab8508190ac321c898cd3df39 |
completed | March 8, 2026, 7:46 a.m. |
Created at: March 1, 2026, 7:56 p.m.