Triple

T20051531
Position Surface form Disambiguated ID Type / Status
Subject Seongdong District E499210 entity
Predicate hasRomanization P2508 FINISHED
Object Seongdong-gu 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: Seongdong-gu | Statement: [Seongdong District, hasRomanization, Seongdong-gu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seongdong-gu
Context triple: [Seongdong District, hasRomanization, Seongdong-gu]
  • A. Seongdong District chosen
    Seongdong District is an urban ward in eastern central Seoul, South Korea, known for its mix of residential neighborhoods, commercial areas, and redevelopment zones along the Han River.
  • B. Seongbuk-gu
    Seongbuk-gu is a district in northern Seoul, South Korea, known for its residential neighborhoods, cultural sites, and several major universities.
  • C. Yongsan-gu
    Yongsan-gu is a central district of Seoul, South Korea, known for its diverse neighborhoods, major transportation hubs, and significant commercial and cultural centers.
  • D. Eunpyeong-gu
    Eunpyeong-gu is a district in northwestern Seoul, South Korea, known for its mix of urban residential areas and access to nearby mountains and temples.
  • E. Gangseo-gu
    Gangseo-gu is a western district of Seoul, South Korea, known for its residential neighborhoods, transportation hubs, and proximity to Gimpo International Airport.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6632ee4d48190b9de3a1efa064492 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:38 p.m.