Triple

T10730386
Position Surface form Disambiguated ID Type / Status
Subject Jungbu Expressway E253055 entity
Predicate connectsCity P4245 FINISHED
Object Seongnam E408723 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: Seongnam | Statement: [Jungbu Expressway, connectsCity, Seongnam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seongnam
Context triple: [Jungbu Expressway, connectsCity, Seongnam]
  • A. Seongnam chosen
    Seongnam is a major satellite city of Seoul in South Korea, known for its planned urban development and role as a residential and commercial hub.
  • B. Suwon
    Suwon is a major South Korean city best known for its UNESCO-listed Hwaseong Fortress and as a key cultural and economic center just south of Seoul.
  • C. Dongducheon
    Dongducheon is a city in northern South Korea known for its proximity to the Demilitarized Zone and the presence of U.S. military bases.
  • D. Yongin
    Yongin is a rapidly growing city in the Seoul Capital Area of South Korea, known for attractions like Everland Resort and the Korean Folk Village.
  • E. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fcb1cd881909635def59ad5d19c completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f61e2fa3bc81909edef00c61265c55 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:14 p.m.