Triple

T5575211
Position Surface form Disambiguated ID Type / Status
Subject Jongno-gu E146300 entity
Predicate hasMountain P10602 FINISHED
Object Bugaksan
Bugaksan is a prominent mountain in central Seoul, South Korea, known for its historical city walls, scenic hiking trails, and views over the capital.
 E533625 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: Bugaksan | Statement: [Jongno-gu, hasMountain, Bugaksan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bugaksan
Context triple: [Jongno-gu, hasMountain, Bugaksan]
  • A. Bansin
    Bansin is a seaside resort town on Germany’s Baltic Sea coast, known as one of the “Kaiserbäder” (Imperial Spas) on the island of Usedom.
  • B. Bar Kosiba
    Bar Kosiba is another name for Simon bar Kokhba, the Jewish military leader who led the Bar Kokhba revolt against the Roman Empire in the 2nd century CE.
  • C. Gardabani
    Gardabani is a town in southeastern Georgia known for its role as an industrial and energy hub within the Kvemo Kartli region.
  • D. Barkot
    Barkot is a small town in Uttarkashi district of Uttarakhand, India, that serves as an important stopover and base for pilgrims traveling to the Yamunotri temple in the Garhwal Himalayas.
  • E. Horki
    Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
  • 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: Bugaksan
Triple: [Jongno-gu, hasMountain, Bugaksan]
Generated description
Bugaksan is a prominent mountain in central Seoul, South Korea, known for its historical city walls, scenic hiking trails, and views over the capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bugaksan
Target entity description: Bugaksan is a prominent mountain in central Seoul, South Korea, known for its historical city walls, scenic hiking trails, and views over the capital.
  • A. Bansin
    Bansin is a seaside resort town on Germany’s Baltic Sea coast, known as one of the “Kaiserbäder” (Imperial Spas) on the island of Usedom.
  • B. Bar Kosiba
    Bar Kosiba is another name for Simon bar Kokhba, the Jewish military leader who led the Bar Kokhba revolt against the Roman Empire in the 2nd century CE.
  • C. Gardabani
    Gardabani is a town in southeastern Georgia known for its role as an industrial and energy hub within the Kvemo Kartli region.
  • D. Barkot
    Barkot is a small town in Uttarkashi district of Uttarakhand, India, that serves as an important stopover and base for pilgrims traveling to the Yamunotri temple in the Garhwal Himalayas.
  • E. Horki
    Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02067e8d8819090a006cb266da5fe completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c02852a6fc8190a543508ab3237f95 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c0430e51fc819084706f52a815350a completed March 22, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_69c046e54a20819080eef5179f206314 completed March 22, 2026, 7:45 p.m.
Created at: March 22, 2026, 3:37 p.m.