Triple

T7172255
Position Surface form Disambiguated ID Type / Status
Subject Dalseo District E167227 entity
Predicate partOf P40 FINISHED
Object Daegu Metropolitan City E27919 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: Daegu Metropolitan City | Statement: [Dalseo District, partOf, Daegu Metropolitan City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daegu Metropolitan City
Context triple: [Dalseo District, partOf, Daegu Metropolitan City]
  • A. Daegu chosen
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • B. Busan metropolitan area
    The Busan metropolitan area is a major South Korean urban and economic hub centered on the port city of Busan, known for its extensive transportation links, coastal location, and role as a key gateway for international trade.
  • C. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • D. Incheon
    Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
  • E. Gijeon
    Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88b0a448190a19bd2d9e2a310a4 completed March 27, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d5a92795cc819087578d02c2c791e4 completed April 8, 2026, 1:02 a.m.
Created at: March 27, 2026, 2:48 p.m.