Triple

T6688065
Position Surface form Disambiguated ID Type / Status
Subject Daejeon Station E152149 entity
Predicate serves P98 FINISHED
Object Mugunghwa-ho E190966 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: Mugunghwa-ho | Statement: [Daejeon Station, serves, Mugunghwa-ho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mugunghwa-ho
Context triple: [Daejeon Station, serves, Mugunghwa-ho]
  • A. Mugunghwa-ho chosen
    Mugunghwa-ho is a class of South Korean intercity passenger trains operated by Korail, known for providing affordable, slower-speed service connecting major cities and regional areas.
  • B. Gukmun
    Gukmun is an old Korean term referring to the native Korean writing system that later came to be known as Joseongeul or Hangul.
  • C. Gwan-eum
    Gwan-eum is the Korean name for Guanyin, the bodhisattva of compassion widely revered in East Asian Buddhism.
  • D. Hyeonreung
    Hyeonreung is a royal tomb from Korea’s Joseon Dynasty, notable as one of the UNESCO-listed burial sites of its kings and queens.
  • E. Junggumun
    Junggumun is a historical writing system used in Korea that incorporated Chinese characters to represent Korean grammatical elements and sounds.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14e58708190a4ba8ff1c085f160 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b31fa0819089c4debbbbce9d22 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:04 p.m.