Triple

T6570299
Position Surface form Disambiguated ID Type / Status
Subject Yeonsu District E155416 entity
Predicate borderedBy P224 FINISHED
Object Namdong District E158074 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: Namdong District | Statement: [Yeonsu District, borderedBy, Namdong District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namdong District
Context triple: [Yeonsu District, borderedBy, Namdong District]
  • A. Namdong District chosen
    Namdong District is a major administrative and commercial hub of Incheon, South Korea, known for housing the city hall and various industrial and residential areas.
  • B. Bupyeong District
    Bupyeong District is a populous urban district of Incheon, South Korea, known as a major residential, commercial, and transportation hub in the metropolitan area.
  • C. Suyeong District
    Suyeong District is an urban coastal district in Busan, South Korea, known for its beaches, residential areas, and cultural attractions.
  • D. Taesong District
    Taesong District is an administrative district of Pyongyang, North Korea, known for hosting major educational and cultural institutions.
  • E. Yeonje District
    Yeonje District is an urban administrative district located in the central area of Busan, South Korea, known for its residential neighborhoods and transportation links.
  • 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_69c688151254819080387f87deab8fa7 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae5791e881909d0b340aa63c6223 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769ddf9e08190b64216fa37d6ca19 completed March 28, 2026, 5:40 a.m.
Created at: March 27, 2026, 1:53 p.m.