Triple

T12158284
Position Surface form Disambiguated ID Type / Status
Subject Kangseo-gu E289635 entity
Predicate partOf P40 FINISHED
Object Seoul Special City E145879 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: Seoul Special City | Statement: [Kangseo-gu, partOf, Seoul Special City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul Special City
Context triple: [Kangseo-gu, partOf, Seoul Special City]
  • A. Seoul Special City chosen
    Seoul Special City is the capital and largest metropolis of South Korea, serving as the country’s political, economic, and cultural center.
  • B. Itaewon
    Itaewon is a vibrant multicultural district in Seoul known for its international cuisine, nightlife, and diverse expatriate community.
  • C. Suwon
    Suwon is a major South Korean city best known for its UNESCO-listed Hwaseong Fortress and as a key cultural and economic center just south of Seoul.
  • D. Gangdong-dong
    Gangdong-dong is a neighborhood in Busan, South Korea, serving as the central administrative hub of the city's Gangseo District.
  • E. Korea Way
    Korea Way is a vibrant stretch of Manhattan known for its dense concentration of Korean restaurants, shops, and cultural businesses, forming the core of New York City's Koreatown.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c277e481908351bf4e664dda42 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f69e8498819080d571e6fb4edfde completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.