Triple
T16872072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uijeongbu |
E421193
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Dobongsan
Dobongsan is a prominent, rocky mountain in northern South Korea known for its scenic hiking trails, granite peaks, and location within Bukhansan National Park.
|
E1237686
|
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: Dobongsan | Statement: [Uijeongbu, hasMountain, Dobongsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dobongsan Context triple: [Uijeongbu, hasMountain, Dobongsan]
-
A.
Gwanggyo Mountain
Gwanggyo Mountain is a prominent natural landmark in South Korea known for its hiking trails and scenic views near the city of Suwon.
-
B.
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.
-
C.
Baegunsan
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
-
D.
Namsan
Namsan is a prominent central mountain in Seoul, South Korea, known for its panoramic city views and the iconic N Seoul Tower.
-
E.
Ok-dong
Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
- 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: Dobongsan Triple: [Uijeongbu, hasMountain, Dobongsan]
Generated description
Dobongsan is a prominent, rocky mountain in northern South Korea known for its scenic hiking trails, granite peaks, and location within Bukhansan National Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dobongsan Target entity description: Dobongsan is a prominent, rocky mountain in northern South Korea known for its scenic hiking trails, granite peaks, and location within Bukhansan National Park.
-
A.
Gwanggyo Mountain
Gwanggyo Mountain is a prominent natural landmark in South Korea known for its hiking trails and scenic views near the city of Suwon.
-
B.
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.
-
C.
Baegunsan
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
-
D.
Namsan
Namsan is a prominent central mountain in Seoul, South Korea, known for its panoramic city views and the iconic N Seoul Tower.
-
E.
Ok-dong
Ok-dong is a neighborhood in Ulsan, South Korea, known for encompassing the large urban green space of Ulsan Grand Park.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f31b448190a21e3e4d1a0d2f73 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2b0dcbc8190a164cbd57586ac9c |
completed | May 10, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_6a00c345229481909d8c0b8a122266bb |
completed | May 10, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c42315448190aecedc58fa0b7319 |
completed | May 10, 2026, 5:45 p.m. |
Created at: April 10, 2026, 5:29 a.m.