Triple
T21584666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mapo District |
E532616
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sogang 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: Sogang University | Statement: [Mapo District, contains, Sogang University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sogang University Context triple: [Mapo District, contains, Sogang University]
-
A.
Sogang University
chosen
Sogang University is a leading private research university in Seoul, South Korea, known for its strong humanities, social sciences, and business programs.
-
B.
Sejong University
Sejong University is a private research university in Seoul, South Korea, known for its strong programs in hospitality, tourism, animation, and engineering.
-
C.
Chosun University
Chosun University is a major private research university in South Korea known for its comprehensive academic programs and regional influence.
-
D.
Chung-Ang University
Chung-Ang University is a major private research university in Seoul, South Korea, renowned for its strong programs in the arts, film, and media studies.
-
E.
Yonsei University
Yonsei University is one of South Korea’s leading private research universities, renowned for its strong international programs and membership in prestigious global academic networks.
- 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb5f2cc0819095552de70eb2ad8d |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 16, 2026, 6:31 p.m.