Triple
T10300324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anyang |
E241609
|
entity |
| Predicate | hasNearbyMountain |
P651
|
FINISHED |
| Object |
Samseongsan
Samseongsan is a mountain in South Korea known for its hiking trails and views over the Anyang and southern Seoul metropolitan area.
|
E856392
|
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: Samseongsan | Statement: [Anyang, hasNearbyMountain, Samseongsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samseongsan Context triple: [Anyang, hasNearbyMountain, Samseongsan]
-
A.
Namsan
Namsan is a prominent central mountain in Seoul, South Korea, known for its panoramic city views and the iconic N Seoul Tower.
-
B.
N Seoul Tower
N Seoul Tower is a prominent communication and observation tower on Namsan Mountain that serves as one of Seoul’s most recognizable cityscape landmarks and tourist attractions.
-
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.
Seongsan Ilchulbong
Seongsan Ilchulbong is a dramatic tuff cone crater on the eastern coast of Jeju Island in South Korea, famed for its sunrise views and unique volcanic landscape.
-
E.
Baegunsan
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
- 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: Samseongsan Triple: [Anyang, hasNearbyMountain, Samseongsan]
Generated description
Samseongsan is a mountain in South Korea known for its hiking trails and views over the Anyang and southern Seoul metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samseongsan Target entity description: Samseongsan is a mountain in South Korea known for its hiking trails and views over the Anyang and southern Seoul metropolitan area.
-
A.
Namsan
Namsan is a prominent central mountain in Seoul, South Korea, known for its panoramic city views and the iconic N Seoul Tower.
-
B.
N Seoul Tower
N Seoul Tower is a prominent communication and observation tower on Namsan Mountain that serves as one of Seoul’s most recognizable cityscape landmarks and tourist attractions.
-
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.
Seongsan Ilchulbong
Seongsan Ilchulbong is a dramatic tuff cone crater on the eastern coast of Jeju Island in South Korea, famed for its sunrise views and unique volcanic landscape.
-
E.
Baegunsan
Baegunsan is a mountain located in or near the city of Uiwang in South Korea, known for its hiking trails and natural scenery.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d3f2c2c8190a71e4a896d8753e7 |
completed | April 9, 2026, 3:30 a.m. |
| NEDg | Description generation | batch_69d7318402f08190b655bdddbd97ecb9 |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d734473ef48190852dbe48742a4273 |
completed | April 9, 2026, 5:08 a.m. |
Created at: April 6, 2026, 11:44 a.m.