Triple
T7376802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Ulsan |
E170145
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Nam-gu, Ulsan |
E605538
|
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: Nam-gu, Ulsan | Statement: [University of Ulsan, locatedIn, Nam-gu, Ulsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nam-gu, Ulsan Context triple: [University of Ulsan, locatedIn, Nam-gu, Ulsan]
-
A.
Nam-gu, Ulsan
chosen
Nam-gu, Ulsan is a coastal district in the metropolitan city of Ulsan, South Korea, known for its industrial facilities and maritime heritage.
-
B.
Nam-gu, Busan
Nam-gu, Busan is a coastal district in the south-central part of Busan, South Korea, known for its residential neighborhoods, universities, and views over the city and harbor.
-
C.
Mokneung
Mokneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
D.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
-
E.
Siheung
Siheung is a coastal city in northwestern South Korea known for its industrial complexes, wetlands, and proximity to Seoul.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a8b18c8190ad1a19521eda2319 |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83437dd28819088c17cfd7dea2e5b |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:07 p.m.