Triple

T6161397
Position Surface form Disambiguated ID Type / Status
Subject High Courts of South Korea E137450 entity
Predicate hasSeatIn P3522 FINISHED
Object Suwon E401676 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: Suwon | Statement: [High Courts of South Korea, hasSeatIn, Suwon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suwon
Context triple: [High Courts of South Korea, hasSeatIn, Suwon]
  • A. Suwon chosen
    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.
  • B. 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.
  • C. Uijeongbu
    Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
  • D. Sangil
    Sangil are an indigenous Moro ethnolinguistic group of the southern Philippines and nearby Indonesian islands, known for their seafaring traditions and Islamic faith.
  • E. 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.
  • 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_69c008a54fc88190b6ce4416490ca79d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d371484819090c18b62b095b49e completed March 22, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6384fece08190ba78bf08d7ee5d4a completed March 27, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:17 p.m.