Triple

T19881788
Position Surface form Disambiguated ID Type / Status
Subject Namsan E477792 entity
Predicate locatedIn P40 FINISHED
Object Yongsan District, Seoul 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: Yongsan District, Seoul | Statement: [Namsan, locatedIn, Yongsan District, Seoul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yongsan District, Seoul
Context triple: [Namsan, locatedIn, Yongsan District, Seoul]
  • A. Seocho District, Seoul
    Seocho District, Seoul is a major affluent residential and business district in southern Seoul known for its legal institutions, cultural venues, and proximity to the Gangnam area.
  • B. Yeongdeungpo District, Seoul
    Yeongdeungpo District, Seoul is a major commercial and residential area in southwestern Seoul, known for its business centers, shopping complexes, and dense urban development.
  • C. Dobong District, Seoul
    Dobong District is a northern residential and mountainous borough of Seoul, South Korea, known for Dobongsan Mountain and its hiking trails.
  • D. Gangseo District, Seoul
    Gangseo District, Seoul is a western administrative district of South Korea’s capital known for its mix of residential areas, educational and cultural institutions, and proximity to Gimpo International Airport.
  • E. Guro District, Seoul
    Guro District, Seoul is a southwestern administrative district of South Korea’s capital known for its digital industrial complexes and technology-focused business centers.
  • 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: Yongsan District, Seoul
Target entity description: Yongsan District, Seoul is a central urban district of South Korea’s capital known for its major transportation hubs, international neighborhoods, and prominent landmarks including government, commercial, and cultural sites.
  • A. Seocho District, Seoul
    Seocho District, Seoul is a major affluent residential and business district in southern Seoul known for its legal institutions, cultural venues, and proximity to the Gangnam area.
  • B. Yeongdeungpo District, Seoul
    Yeongdeungpo District, Seoul is a major commercial and residential area in southwestern Seoul, known for its business centers, shopping complexes, and dense urban development.
  • C. Dobong District, Seoul
    Dobong District is a northern residential and mountainous borough of Seoul, South Korea, known for Dobongsan Mountain and its hiking trails.
  • D. Gangseo District, Seoul
    Gangseo District, Seoul is a western administrative district of South Korea’s capital known for its mix of residential areas, educational and cultural institutions, and proximity to Gimpo International Airport.
  • E. Guro District, Seoul
    Guro District, Seoul is a southwestern administrative district of South Korea’s capital known for its digital industrial complexes and technology-focused business centers.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658df3f5c81909b5b290de91b8d50 completed April 20, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:52 p.m.