Triple

T11831905
Position Surface form Disambiguated ID Type / Status
Subject Songdo Campus E281410 entity
Predicate countrySubdivision P766 FINISHED
Object Incheon Metropolitan City E27787 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: Incheon Metropolitan City | Statement: [Songdo Campus, countrySubdivision, Incheon Metropolitan City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Incheon Metropolitan City
Context triple: [Songdo Campus, countrySubdivision, Incheon Metropolitan City]
  • A. Incheon chosen
    Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
  • B. Busan metropolitan area
    The Busan metropolitan area is a major South Korean urban and economic hub centered on the port city of Busan, known for its extensive transportation links, coastal location, and role as a key gateway for international trade.
  • C. Sejong City
    Sejong City is South Korea’s planned administrative capital, designed to house numerous government ministries and ease congestion in Seoul.
  • D. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62c95988190a45dbaa7001c8846 completed April 10, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd27ee6ff881909fb0d1590580c4e8 completed May 8, 2026, 12:01 a.m.
Created at: April 8, 2026, 9:43 p.m.