Triple

T6980001
Position Surface form Disambiguated ID Type / Status
Subject Gyeyang District E161816 entity
Predicate connectedTo P37 FINISHED
Object Seoul metropolitan area E166134 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: Seoul metropolitan area | Statement: [Gyeyang District, connectedTo, Seoul metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul metropolitan area
Context triple: [Gyeyang District, connectedTo, Seoul metropolitan area]
  • A. Seoul Capital Area chosen
    The Seoul Capital Area is South Korea’s largest metropolitan region, encompassing Seoul, Incheon, and surrounding Gyeonggi Province, and serving as the country’s political, economic, and cultural hub.
  • B. Seoul
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • C. Busan Metro urban zone
    The Busan Metro urban zone is the primary fare zone covering the central metropolitan area of Busan’s subway network, encompassing major downtown and commercial districts.
  • D. Yongin
    Yongin is a rapidly growing city in the Seoul Capital Area of South Korea, known for attractions like Everland Resort and the Korean Folk Village.
  • E. Incheon
    Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
  • 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_69c68855dc0481909b4c7e9e9ed273db completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db6c1efc8190ab1575ae2ce726db completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c3c1a408190b2f3cdcf0eea43c7 completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 2:31 p.m.