Triple

T11536184
Position Surface form Disambiguated ID Type / Status
Subject Yoko E273553 entity
Predicate nameElement P27866 FINISHED
Object Ko
Ko is a Japanese given-name element commonly used in female names, often carrying meanings like “child” depending on the kanji used.
 E931374 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: Ko | Statement: [Yoko, nameElement, Ko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ko
Context triple: [Yoko, nameElement, Ko]
  • A. Koja
    Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
  • B. Kok
    Kok is a Dutch surname most notably borne by Wim Kok, a former Prime Minister of the Netherlands.
  • C. Kö
    Kö is the colloquial name for Königsallee, Düsseldorf’s famous luxury shopping boulevard known for its upscale boutiques and central canal.
  • D. Ku
    Ku is a principal Hawaiian god associated with war, politics, and prosperity, widely venerated in traditional Native Hawaiian religion.
  • E. Koo
    Koo is a Korean family name associated with several prominent business and cultural figures in South Korea.
  • 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: Ko
Triple: [Yoko, nameElement, Ko]
Generated description
Ko is a Japanese given-name element commonly used in female names, often carrying meanings like “child” depending on the kanji used.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ko
Target entity description: Ko is a Japanese given-name element commonly used in female names, often carrying meanings like “child” depending on the kanji used.
  • A. Koja
    Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
  • B. Kok
    Kok is a Dutch surname most notably borne by Wim Kok, a former Prime Minister of the Netherlands.
  • C. Kö
    Kö is the colloquial name for Königsallee, Düsseldorf’s famous luxury shopping boulevard known for its upscale boutiques and central canal.
  • D. Ku
    Ku is a principal Hawaiian god associated with war, politics, and prosperity, widely venerated in traditional Native Hawaiian religion.
  • E. Koo
    Koo is a Korean family name associated with several prominent business and cultural figures in South Korea.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8839b4bb48190b748ec4119f36c11 completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6858af0d081909078d5862ec3d469 completed April 20, 2026, 7:59 p.m.
NEDg Description generation batch_69e68fd8210c8190a7b0bbd8a50ff6b1 completed April 20, 2026, 8:43 p.m.
NED2 Entity disambiguation (via description) batch_69e69f12cfcc8190a06e0922c9faa49e completed April 20, 2026, 9:48 p.m.
Created at: April 8, 2026, 9:37 p.m.