Triple

T1322534
Position Surface form Disambiguated ID Type / Status
Subject Daejeon E28250 entity
Predicate hasMountain P10602 FINISHED
Object Gubongsan
Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
 E157918 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: Gubongsan | Statement: [Daejeon, hasMountain, Gubongsan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gubongsan
Context triple: [Daejeon, hasMountain, Gubongsan]
  • A. Bomunsan
    Bomunsan is a prominent mountain and recreational area in Daejeon, South Korea, known for its hiking trails, temples, and city views.
  • B. Gapcheon
    Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
  • C. Yudeungcheon
    Yudeungcheon is a river in Daejeon, South Korea, known for flowing through the city’s urban areas and serving as a local recreational and ecological space.
  • D. 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.
  • E. Baeggu
    Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
  • 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: Gubongsan
Triple: [Daejeon, hasMountain, Gubongsan]
Generated description
Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gubongsan
Target entity description: Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
  • A. Bomunsan
    Bomunsan is a prominent mountain and recreational area in Daejeon, South Korea, known for its hiking trails, temples, and city views.
  • B. Gapcheon
    Gapcheon is a major river flowing through the city of Daejeon in South Korea, serving as a central natural and recreational landmark.
  • C. Yudeungcheon
    Yudeungcheon is a river in Daejeon, South Korea, known for flowing through the city’s urban areas and serving as a local recreational and ecological space.
  • D. 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.
  • E. Baeggu
    Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19b76b48190aa8857b80971a842 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd47471108190b01121b384d871aa completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd6314f488190a56451fae95f863c completed March 8, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69acd68afe10819081bb5991fb007da9 completed March 8, 2026, 1:53 a.m.
Created at: March 1, 2026, 7:55 p.m.