Triple

T22143820
Position Surface form Disambiguated ID Type / Status
Subject Songpa District E547233 entity
Predicate hasAttraction P105 FINISHED
Object Seokchon Lake NE NERFINISHED

How this triple was built (2 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: Seokchon Lake | Statement: [Songpa District, hasAttraction, Seokchon Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seokchon Lake
Context triple: [Songpa District, hasAttraction, Seokchon Lake]
  • A. Seokchon Lake chosen
    Seokchon Lake is a scenic artificial lake and popular recreational area in southeastern Seoul, known for its walking paths, cherry blossoms, and views of nearby Lotte World attractions.
  • B. Gongjicheon Lake
    Gongjicheon Lake is a scenic body of water in Chuncheon, South Korea, known for its riverside parks, walking paths, and seasonal festivals.
  • C. Sanjeong Lake
    Sanjeong Lake is a scenic highland lake in Pocheon, South Korea, known for its forested mountains, walking trails, and seasonal views that attract many visitors.
  • D. Chungju Lake
    Chungju Lake is a large artificial reservoir in South Korea, created by the Chungju Dam and known for its scenic landscapes and recreational activities.
  • E. Suseong Lake
    Suseong Lake is a popular recreational lake in Daegu, South Korea, known for its scenic walking paths, cafes, and cultural events.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129c045448190b3d189cdb8c0d2fd completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.