Triple

T7499017
Position Surface form Disambiguated ID Type / Status
Subject Nam District (Busan) E177211 entity
Predicate hasMcCuneReischauerRomanization P23170 FINISHED
Object Nam-ku
Nam-ku is the McCune–Reischauer romanization of Nam District, an administrative district in the city of Busan, South Korea.
E669116 NE FINISHED

How this triple was built (4 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: Nam-ku | Statement: [Nam District (Busan), hasMcCuneReischauerRomanization, Nam-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nam-ku
Context triple: [Nam District (Busan), hasMcCuneReischauerRomanization, Nam-ku]
  • A. Hosuni
    Hosuni is the female tiger mascot character created as the sibling counterpart to Hodori, the official mascot of the 1988 Seoul Olympic Games.
  • B. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • C. Shungnak
    Shungnak is a small Inupiat village in northwestern Alaska known for its remote location above the Arctic Circle and traditional subsistence lifestyle.
  • D. Jumong
    Jumong is the legendary founder and first king of the ancient Korean kingdom of Goguryeo, celebrated as a heroic archer and culture hero in Korean history and mythology.
  • E. Koung-Khi
    Koung-Khi is an administrative department located in the West Region of Cameroon.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nam-ku
Triple: [Nam District (Busan), hasMcCuneReischauerRomanization, Nam-ku]
Generated description
Nam-ku is the McCune–Reischauer romanization of Nam District, an administrative district in the city of Busan, South Korea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nam-ku
Target entity description: Nam-ku is the McCune–Reischauer romanization of Nam District, an administrative district in the city of Busan, South Korea.
  • A. Hosuni
    Hosuni is the female tiger mascot character created as the sibling counterpart to Hodori, the official mascot of the 1988 Seoul Olympic Games.
  • B. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • C. Shungnak
    Shungnak is a small Inupiat village in northwestern Alaska known for its remote location above the Arctic Circle and traditional subsistence lifestyle.
  • D. Jumong
    Jumong is the legendary founder and first king of the ancient Korean kingdom of Goguryeo, celebrated as a heroic archer and culture hero in Korean history and mythology.
  • E. Koung-Khi
    Koung-Khi is an administrative department located in the West Region of Cameroon.
  • F. None of above. chosen

Provenance (5 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f597a0c08190b34fa283a11d98c7 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c8b28d0819095c7b666d442c7ab completed March 28, 2026, 8:39 p.m.
NEDg Description generation batch_69c83d49547081909028ac0293dae102 completed March 28, 2026, 8:42 p.m.
NED2 Entity disambiguation (via description) batch_69c8410c22bc8190a1f52179bf3c720b completed March 28, 2026, 8:58 p.m.
Created at: March 27, 2026, 3:44 p.m.