Triple

T10043648
Position Surface form Disambiguated ID Type / Status
Subject Suyeong River E205356 entity
Predicate flowsThrough P225 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 River, flowsThrough, Suyeong District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suyeong District
Context triple: [Suyeong River, flowsThrough, 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf61b3e08190b69bcf67b6a95342 completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbac7a42348190a86fa5a97e3d36ca completed April 12, 2026, 2:30 p.m.
Created at: March 30, 2026, 8:55 p.m.