Triple
T9413080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uiwang |
E226750
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Baegunsan
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
|
E797484
|
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: Baegunsan | Statement: [Uiwang, hasMountain, Baegunsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baegunsan Context triple: [Uiwang, hasMountain, Baegunsan]
-
A.
Gyeryongsan
Gyeryongsan is a prominent mountain in central South Korea known for its scenic national park, rich biodiversity, and cultural sites including historic Buddhist temples.
-
B.
Geumjeongsan
Geumjeongsan is a prominent mountain in Busan, South Korea, known for its scenic hiking trails, historic fortress walls, and cultural sites.
-
C.
Ok-dong
Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
-
D.
Hwangnyeongsan Mountain
Hwangnyeongsan Mountain is a prominent peak in Busan, South Korea, known for its panoramic city and coastal views, especially popular at night.
-
E.
Umyeonsan Mountain
Umyeonsan Mountain is a low, forested peak in southern Seoul, South Korea, known for its hiking trails, city views, and role as a natural green space within the urban area.
- 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: Baegunsan Triple: [Uiwang, hasMountain, Baegunsan]
Generated description
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baegunsan Target entity description: Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
-
A.
Gyeryongsan
Gyeryongsan is a prominent mountain in central South Korea known for its scenic national park, rich biodiversity, and cultural sites including historic Buddhist temples.
-
B.
Geumjeongsan
Geumjeongsan is a prominent mountain in Busan, South Korea, known for its scenic hiking trails, historic fortress walls, and cultural sites.
-
C.
Ok-dong
Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
-
D.
Hwangnyeongsan Mountain
Hwangnyeongsan Mountain is a prominent peak in Busan, South Korea, known for its panoramic city and coastal views, especially popular at night.
-
E.
Umyeonsan Mountain
Umyeonsan Mountain is a low, forested peak in southern Seoul, South Korea, known for its hiking trails, city views, and role as a natural green space within the urban area.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5258f7e081908d48600409181fdb |
completed | April 1, 2026, 5:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b0f9648190894a4cd13d7e5fb5 |
completed | April 4, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69d108466fb481909682fcaac354b312 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d108be82888190b0ec08119cd00b68 |
completed | April 4, 2026, 12:49 p.m. |
Created at: March 30, 2026, 7:47 p.m.