Triple

T10899799
Position Surface form Disambiguated ID Type / Status
Subject Jeonpo-dong E257406 entity
Predicate hasNickname P39 FINISHED
Object Jeonpo Cafe District E257406 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: Jeonpo Cafe District | Statement: [Jeonpo-dong, hasNickname, Jeonpo Cafe District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeonpo Cafe District
Context triple: [Jeonpo-dong, hasNickname, Jeonpo Cafe District]
  • A. Jeonpo-dong chosen
    Jeonpo-dong is a neighborhood in Busan, South Korea, known for its trendy cafes, boutiques, and vibrant urban culture.
  • B. Cheongnyang-eup
    Cheongnyang-eup is a town-level administrative division located within Ulju County in Ulsan, South Korea.
  • C. Gwangsan District
    Gwangsan District is one of the administrative districts of Gwangju, South Korea, known for its mix of urban development and transportation hubs including Gwangju Songjeong station.
  • D. Yeongjong District
    Yeongjong District is a major development area within Incheon, South Korea, centered around Incheon International Airport and planned as a hub for logistics, tourism, and high-tech industries.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d761a2392c8190bc2c2359d63eff7a completed April 9, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69e216b417bc8190b35477e9d363a289 completed April 17, 2026, 11:17 a.m.
Created at: April 8, 2026, 9:21 p.m.