Triple

T21623000
Position Surface form Disambiguated ID Type / Status
Subject Jongno-gu Office E533623 entity
Predicate locatedInCapital P5025 FINISHED
Object Seoul, capital of South Korea NE NERFINISHED

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, capital of South Korea | Statement: [Jongno-gu Office, locatedInCapital, Seoul, capital of South Korea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul, capital of South Korea
Context triple: [Jongno-gu Office, locatedInCapital, Seoul, capital of South Korea]
  • A. Seoul chosen
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • B. Jung-gu, Seoul
    Jung-gu, Seoul is a central district of South Korea’s capital city, known for its major commercial areas, historic sites, and key government and business institutions.
  • C. Suwon, South Korea
    Suwon, South Korea is a major city just south of Seoul known for its high-tech industry and the UNESCO-listed Hwaseong Fortress.
  • D. Sejong City
    Sejong City is South Korea’s planned administrative capital, designed to house numerous government ministries and ease congestion in Seoul.
  • E. Daejeon, South Korea
    Daejeon, South Korea is a major inland city known as a national hub for science, technology, and research, home to numerous universities, government research institutes, and high-tech industries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c464fba881908d0ff2ac80511ce1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef3bb0c42c8190997fbeb7a764d60e completed April 27, 2026, 10:34 a.m.
Created at: April 16, 2026, 6:34 p.m.