Triple

T5565939
Position Surface form Disambiguated ID Type / Status
Subject Seoul Special City E145879 entity
Predicate nativeName P15 FINISHED
Object 서울특별시 E19209 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: 서울특별시 | Statement: [Seoul Special City, nativeName, 서울특별시]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 서울특별시
Context triple: [Seoul Special City, nativeName, 서울특별시]
  • A. Seoul Capital Area
    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 chosen
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • C. 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.
  • D. Gyeonggi Province
    Gyeonggi Province is a populous region in northwestern South Korea that surrounds Seoul and serves as a key political, economic, and military hub of the country.
  • E. 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.
  • 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_69c008fdae24819081aa002ad99cd966 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02034fc3081908920c52a19d462e1 completed March 22, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0284525148190a7bf88c22723552a completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:36 p.m.