Triple

T14762578
Position Surface form Disambiguated ID Type / Status
Subject Seodaemun-gu E346906 entity
Predicate contains P35 FINISHED
Object Sinchon-dong E344372 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: Sinchon-dong | Statement: [Seodaemun-gu, contains, Sinchon-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinchon-dong
Context triple: [Seodaemun-gu, contains, Sinchon-dong]
  • A. Sinchon-dong chosen
    Sinchon-dong is a vibrant neighborhood in Seoul, South Korea, known for its youthful atmosphere, shopping, nightlife, and concentration of major universities.
  • B. Sinsa-dong
    Sinsa-dong is a fashionable neighborhood in Seoul, South Korea, known for its trendy boutiques, cafes, and the popular Garosu-gil shopping street.
  • C. Cheonghak-dong
    Cheonghak-dong is a neighborhood (dong) located within Dong-gu, one of the central districts of Busan, South Korea.
  • D. Cheonghak-dong
    Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
  • E. Yeocheon-dong
    Yeocheon-dong is a neighborhood in Ulsan, South Korea, known for encompassing the expansive Ulsan Grand Park.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f3a1608190b1b17624003a0c7f completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5dee8988190b80cb487c12bfc2d completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 1:30 a.m.