Triple

T19578321
Position Surface form Disambiguated ID Type / Status
Subject Dangun E489919 entity
Predicate father P120 FINISHED
Object Hwanung 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: Hwanung | Statement: [Dangun, father, Hwanung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hwanung
Context triple: [Dangun, father, Hwanung]
  • A. Hwanung chosen
    Hwanung is a heavenly prince in Korean mythology who descends from the sky to found a sacred city and becomes the father of Dangun, the legendary founder of Gojoseon.
  • B. Seonghwa
    Seonghwa was the era name used during the reign of King Seongjong of the Joseon dynasty in Korea, marking a specific period of his rule.
  • C. Seonghwan
    Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
  • D. Taegwan
    Taegwan is a town and county-level city in North Pyongan Province in northwestern North Korea.
  • E. Jeongdongjin
    Jeongdongjin is a coastal town in South Korea famed for its scenic East Sea sunrise views and seaside railway station.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6402693d88190a828c0e136895783 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:42 p.m.