Triple

T20556550
Position Surface form Disambiguated ID Type / Status
Subject FC Augsburg E504733 entity
Predicate notableFormerPlayer P304 FINISHED
Object Ja-Cheol Koo
Ja-Cheol Koo is a South Korean former professional footballer and attacking midfielder best known for his influential spells in the Bundesliga and his key role with the South Korean national team.
 E1439679 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: Ja-Cheol Koo | Statement: [FC Augsburg, notableFormerPlayer, Ja-Cheol Koo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ja-Cheol Koo
Context triple: [FC Augsburg, notableFormerPlayer, Ja-Cheol Koo]
  • A. Yong-taek Jung
    Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
  • B. Jong Wook Kim
    Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
  • C. Sung-kyu Jung
    Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
  • D. Ho-seok Jung
    Ho-seok Jung is a notable individual recognized for achievements significant enough to be associated with the surname Jung.
  • E. Joon-Soo Oh
    Joon-Soo Oh is the father of Canadian actress Sandra Oh, known for supporting her early artistic ambitions despite initially encouraging a more traditional career path.
  • 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: Ja-Cheol Koo
Triple: [FC Augsburg, notableFormerPlayer, Ja-Cheol Koo]
Generated description
Ja-Cheol Koo is a South Korean former professional footballer and attacking midfielder best known for his influential spells in the Bundesliga and his key role with the South Korean national team.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ja-Cheol Koo
Target entity description: Ja-Cheol Koo is a South Korean former professional footballer and attacking midfielder best known for his influential spells in the Bundesliga and his key role with the South Korean national team.
  • A. Yong-taek Jung
    Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
  • B. Jong Wook Kim
    Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
  • C. Sung-kyu Jung
    Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
  • D. Ho-seok Jung
    Ho-seok Jung is a notable individual recognized for achievements significant enough to be associated with the surname Jung.
  • E. Joon-Soo Oh
    Joon-Soo Oh is the father of Canadian actress Sandra Oh, known for supporting her early artistic ambitions despite initially encouraging a more traditional career path.
  • 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a5de9c008190b8620628fb285e90 completed April 20, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08b3ddd76c8190bf8a7ff3b2820188 completed May 16, 2026, 6:13 p.m.
NEDg Description generation batch_6a08b56160c88190902dd0d7ec7bbedf completed May 16, 2026, 6:20 p.m.
NED2 Entity disambiguation (via description) batch_6a08b5cfc3ac81908c62f48fa7a43aa2 completed May 16, 2026, 6:22 p.m.
Created at: April 16, 2026, 11:38 a.m.