Triple

T5575206
Position Surface form Disambiguated ID Type / Status
Subject Jongno-gu E146300 entity
Predicate borderedBy P224 FINISHED
Object Seongbuk-gu E348269 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: Seongbuk-gu | Statement: [Jongno-gu, borderedBy, Seongbuk-gu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seongbuk-gu
Context triple: [Jongno-gu, borderedBy, Seongbuk-gu]
  • A. 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.
  • B. Chongno-gu
    Chongno-gu is a central district in Seoul, South Korea, known as the historic and cultural heart of the city, home to major palaces, government institutions, and traditional markets.
  • C. Seongbuk District chosen
    Seongbuk District is a residential and educational borough in northern Seoul, South Korea, known for its universities, cultural sites, and traditional neighborhoods.
  • D. Jung-gu
    Jung-gu is a central administrative district of the metropolitan city of Ulsan in South Korea.
  • E. 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.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02067e8d8819090a006cb266da5fe completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d02748c819086f3b66a36201fdc completed March 24, 2026, 4:03 a.m.
Created at: March 22, 2026, 3:37 p.m.