Triple
T6905634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwangnyeongsan |
E159805
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object |
Hwangnyeongsan
Hwangnyeongsan is a mountain in Busan, South Korea, known for its panoramic city views and popular hiking trails.
|
E636866
|
NE FINISHED |
How this triple was built (4 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: Hwangnyeongsan | Statement: [Hwangnyeongsan, romanization, Hwangnyeongsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hwangnyeongsan Context triple: [Hwangnyeongsan, romanization, Hwangnyeongsan]
-
A.
Hwanggujicheon
Hwanggujicheon is a stream in Osan, South Korea, that serves as a local waterway and natural feature of the city’s landscape.
-
B.
Myeongneung
Myeongneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
C.
Anseongcheon
Anseongcheon is a river in South Korea that flows through the city of Pyeongtaek in Gyeonggi Province.
-
D.
Nam-gu
Nam-gu is a central administrative district of the metropolitan city of Ulsan in South Korea, known for its residential areas, commercial centers, and proximity to major industrial complexes.
-
E.
Nam-gu
Nam-gu is a central urban district of Daegu in South Korea, known for its residential neighborhoods, commercial areas, and educational institutions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hwangnyeongsan Triple: [Hwangnyeongsan, romanization, Hwangnyeongsan]
Generated description
Hwangnyeongsan is a mountain in Busan, South Korea, known for its panoramic city views and popular hiking trails.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hwangnyeongsan Target entity description: Hwangnyeongsan is a mountain in Busan, South Korea, known for its panoramic city views and popular hiking trails.
-
A.
Hwanggujicheon
Hwanggujicheon is a stream in Osan, South Korea, that serves as a local waterway and natural feature of the city’s landscape.
-
B.
Myeongneung
Myeongneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
-
C.
Anseongcheon
Anseongcheon is a river in South Korea that flows through the city of Pyeongtaek in Gyeonggi Province.
-
D.
Nam-gu
Nam-gu is a central urban district of Daegu in South Korea, known for its residential neighborhoods, commercial areas, and educational institutions.
-
E.
Nam-gu
Nam-gu is a central administrative district of the metropolitan city of Ulsan in South Korea, known for its residential areas, commercial centers, and proximity to major industrial complexes.
- F. None of above. chosen
Provenance (5 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d98b07f0819093595e958fa0317b |
completed | March 27, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775348f6081909fb869dae0237ca9 |
completed | March 28, 2026, 6:29 a.m. |
| NEDg | Description generation | batch_69c777c607fc81909d73ca6b9c038073 |
completed | March 28, 2026, 6:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7781fe37c81908c28fb9e65c1559b |
completed | March 28, 2026, 6:41 a.m. |
Created at: March 27, 2026, 2:25 p.m.