Triple

T7206798
Position Surface form Disambiguated ID Type / Status
Subject Incheon Gwangyeoksi E148684 entity
Predicate hasDistrict P459 FINISHED
Object Bupyeong District E159653 NE FINISHED

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: Bupyeong District | Statement: [Incheon Gwangyeoksi, hasDistrict, Bupyeong District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bupyeong District
Context triple: [Incheon Gwangyeoksi, hasDistrict, Bupyeong District]
  • A. Bupyeong District chosen
    Bupyeong District is a populous urban district of Incheon, South Korea, known as a major residential, commercial, and transportation hub in the metropolitan area.
  • B. Gwangsan District
    Gwangsan District is one of the administrative districts of Gwangju, South Korea, known for its mix of urban development and transportation hubs including Gwangju Songjeong station.
  • C. Suyeong District
    Suyeong District is an urban coastal district in Busan, South Korea, known for its beaches, residential areas, and cultural attractions.
  • D. Seongbuk District
    Seongbuk District is a residential and educational borough in northern Seoul, South Korea, known for its universities, cultural sites, and traditional neighborhoods.
  • E. Gwangjin District
    Gwangjin District is an eastern borough of Seoul, South Korea, known for its universities, shopping areas, and location along the Han River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c687e8cf188190b5f3ecffd681f04e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e969c5fc819096bc03bfba12d0cf completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c98564d32881908ebdeb2aa41da4f7 completed March 29, 2026, 8:02 p.m.
Created at: March 27, 2026, 2:52 p.m.