Triple

T7206831
Position Surface form Disambiguated ID Type / Status
Subject Yeongjong Island E148685 entity
Predicate administrativeDivisionOf P747 FINISHED
Object Jung-gu, Incheon E648391 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: Jung-gu, Incheon | Statement: [Yeongjong Island, administrativeDivisionOf, Jung-gu, Incheon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jung-gu, Incheon
Context triple: [Yeongjong Island, administrativeDivisionOf, Jung-gu, Incheon]
  • A. Jung District, Incheon chosen
    Jung District, Incheon is a central coastal district of Incheon, South Korea, that includes key areas such as Incheon International Airport and the surrounding islands.
  • B. Seo District, Incheon
    Seo District, Incheon is an administrative district in the western part of Incheon, South Korea, known for its mix of residential areas, industrial zones, and coastal wetlands.
  • C. Gwacheon
    Gwacheon is a small city in South Korea known for hosting major government offices, cultural institutions, and the Seoul Grand Park complex.
  • D. Jung-gu
    Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
  • E. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • 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_69c687e8cf188190b5f3ecffd681f04e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e969c5fc819096bc03bfba12d0cf completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d381a7288190bbfdb8f1de6b5f05 completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:52 p.m.