Triple

T19116969
Position Surface form Disambiguated ID Type / Status
Subject AREX E467931 entity
Predicate openedSection P28341 FINISHED
Object Seoul Station–Gimpo International Airport section NE NERFINISHED

How this triple was built (3 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 Station–Gimpo International Airport section | Statement: [AREX, openedSection, Seoul Station–Gimpo International Airport section]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul Station–Gimpo International Airport section
Context triple: [AREX, openedSection, Seoul Station–Gimpo International Airport section]
  • A. Busan–Ulsan section
    The Busan–Ulsan section is a coastal railway segment in southeastern South Korea that connects the major port city of Busan with the industrial city of Ulsan.
  • B. Suin–Bundang Line
    The Suin–Bundang Line is a major commuter rail line in the Seoul metropolitan area that connects southeastern Seoul with surrounding cities such as Seongnam, Yongin, and Suwon.
  • C. Ulsan–Pohang section
    The Ulsan–Pohang section is a coastal railway segment in South Korea connecting the cities of Ulsan and Pohang as part of the Donghae Line.
  • D. Shinbundang Line
    The Shinbundang Line is a high-speed, driverless subway line in the Seoul metropolitan area that connects southern Seoul with the satellite city of Bundang.
  • E. Pohang–Samcheok section
    The Pohang–Samcheok section is a coastal railway segment in South Korea connecting the cities of Pohang and Samcheok along the Donghae Line.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Seoul Station–Gimpo International Airport section
Target entity description: The Seoul Station–Gimpo International Airport section is the central urban stretch of South Korea’s AREX rail line, linking downtown Seoul with one of the capital’s main airports.
  • A. Busan–Ulsan section
    The Busan–Ulsan section is a coastal railway segment in southeastern South Korea that connects the major port city of Busan with the industrial city of Ulsan.
  • B. Suin–Bundang Line
    The Suin–Bundang Line is a major commuter rail line in the Seoul metropolitan area that connects southeastern Seoul with surrounding cities such as Seongnam, Yongin, and Suwon.
  • C. Ulsan–Pohang section
    The Ulsan–Pohang section is a coastal railway segment in South Korea connecting the cities of Ulsan and Pohang as part of the Donghae Line.
  • D. Shinbundang Line
    The Shinbundang Line is a high-speed, driverless subway line in the Seoul metropolitan area that connects southern Seoul with the satellite city of Bundang.
  • E. Pohang–Samcheok section
    The Pohang–Samcheok section is a coastal railway segment in South Korea connecting the cities of Pohang and Samcheok along the Donghae Line.
  • F. None of above. chosen

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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e399a6d8819090a9501ff1637b9d completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.