Triple

T7780896
Position Surface form Disambiguated ID Type / Status
Subject Suyeong-dong E221512 entity
Predicate locatedIn P40 FINISHED
Object Suyeong District E33247 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: Suyeong District | Statement: [Suyeong-dong, locatedIn, Suyeong District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suyeong District
Context triple: [Suyeong-dong, locatedIn, Suyeong District]
  • A. Suyeong District chosen
    Suyeong District is an urban coastal district in Busan, South Korea, known for its beaches, residential areas, and cultural attractions.
  • B. 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.
  • C. Gwangjin District
    Gwangjin District is an eastern borough of Seoul, South Korea, known for its universities, shopping areas, and location along the Han River.
  • 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. Geumjeong District
    Geumjeong District is an administrative district in the northeastern part of Busan, South Korea, known for its mountainous terrain, historic fortress, and educational institutions.
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d6cf9881909f5220437db13cc7 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb137f224881908731d47547584a8e completed March 31, 2026, 12:21 a.m.
Created at: March 30, 2026, 4:20 p.m.