Triple

T14576256
Position Surface form Disambiguated ID Type / Status
Subject Itu Aba Island E342058 entity
Predicate partOf P40 FINISHED
Object Cijin District E356238 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: Cijin District | Statement: [Itu Aba Island, partOf, Cijin District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cijin District
Context triple: [Itu Aba Island, partOf, Cijin District]
  • A. Cijin District chosen
    Cijin District is a coastal district of Kaohsiung, Taiwan, known for its historic port, seafood markets, and popular seaside attractions.
  • B. Dongnae District
    Dongnae District is a historic and central administrative district of Busan, South Korea, known for its hot springs and cultural heritage sites.
  • C. Busanjin District
    Busanjin District is a central urban district of Busan, South Korea, known as a major commercial and transportation hub of the city.
  • D. Bupyeong District
    Bupyeong District is a populous urban district of Incheon, South Korea, known as a major residential, commercial, and transportation hub in the metropolitan area.
  • E. Busan Jung District
    Busan Jung District is a central urban district of Busan, South Korea, known for its historic downtown area, bustling commercial streets, and major shopping and cultural attractions.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f5ec448190b2ef887fdf7b633e completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24a2fc048190b68d3267fe17471b completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:24 a.m.