Triple

T6023577
Position Surface form Disambiguated ID Type / Status
Subject Qiaokou District E134120 entity
Predicate borders P224 FINISHED
Object Hanyang District E78480 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: Hanyang District | Statement: [Qiaokou District, borders, Hanyang District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanyang District
Context triple: [Qiaokou District, borders, Hanyang District]
  • A. Hanyang District chosen
    Hanyang District is an urban district of Wuhan, China, situated at the confluence of the Yangtze and Han rivers and known as one of the city’s historic core areas.
  • B. Gwangjin District
    Gwangjin District is an eastern borough of Seoul, South Korea, known for its universities, shopping areas, and location along the Han River.
  • C. Seongbuk District
    Seongbuk District is a residential and educational borough in northern Seoul, South Korea, known for its universities, cultural sites, and traditional neighborhoods.
  • D. Taesong District
    Taesong District is an administrative district of Pyongyang, North Korea, known for hosting major educational and cultural institutions.
  • E. 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.
  • 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_69c008742a5c8190b9cb9c2787a3d8b3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04fbd7978819085d683578bc62aa3 completed March 22, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c63849a59881909e32c0271b4beb51 completed March 27, 2026, 7:56 a.m.
Created at: March 22, 2026, 4:07 p.m.