Triple

T21257862
Position Surface form Disambiguated ID Type / Status
Subject Namgang River E523915 entity
Predicate nameInKorean P17869 FINISHED
Object 남강 NE NERFINISHED

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: 남강 | Statement: [Namgang River, nameInKorean, 남강]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 남강
Context triple: [Namgang River, nameInKorean, 남강]
  • A. Nam-gu
    Nam-gu is a central administrative district of the metropolitan city of Ulsan in South Korea, known for its residential areas, commercial centers, and proximity to major industrial complexes.
  • B. Nam-gu
    Nam-gu is a central urban district of Daegu in South Korea, known for its residential neighborhoods, commercial areas, and educational institutions.
  • C. Nam-gu
    Nam-gu is a coastal district in the southeastern South Korean city of Busan, known for its residential areas, universities, and seaside parks.
  • D. Nam-gu
    Nam-gu is an administrative district (gu) of the coastal city of Pohang in North Gyeongsang Province, South Korea.
  • E. Namgang River chosen
    The Namgang River is a scenic waterway in South Korea known for flowing through Jinju and hosting the famous Jinju Namgang Yudeung (Lantern) Festival.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5146c108190adc9adb73e90abff completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e735e2f1d48190b566ab4d736fdbc4 completed April 21, 2026, 8:31 a.m.
Created at: April 16, 2026, 3:58 p.m.