Triple

T12648714
Position Surface form Disambiguated ID Type / Status
Subject Ruan Louw E302098 entity
Predicate hasGivenName P17 FINISHED
Object Ruan
Ruan is a masculine given name commonly used in South Africa and other regions, often of Afrikaans or Chinese origin depending on cultural context.
 E994394 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: Ruan | Statement: [Ruan Louw, hasGivenName, Ruan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ruan
Context triple: [Ruan Louw, hasGivenName, Ruan]
  • A. Ruian
    Ruian is a county-level coastal city administered by Wenzhou in Zhejiang Province, China, known for its private entrepreneurship and light manufacturing industries.
  • B. Róng
    Róng is the endonym used by the Lepcha people to refer to their own language spoken primarily in parts of India, Bhutan, and Nepal.
  • C. Maonan
    The Maonan are a small ethnic minority group in southern China known for their distinct Kam–Sui language, traditional rice farming, and rich folk customs.
  • D. Zuoren
    Zuoren is the given name of Zhou Zuoren, a prominent 20th-century Chinese essayist, translator, and literary critic.
  • E. Rushan
    Rushan is a county-level coastal city in eastern Shandong Province, China, known for its fishing industry, beaches, and marine-based economy.
  • 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: Ruan
Triple: [Ruan Louw, hasGivenName, Ruan]
Generated description
Ruan is a masculine given name commonly used in South Africa and other regions, often of Afrikaans or Chinese origin depending on cultural context.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ruan
Target entity description: Ruan is a masculine given name commonly used in South Africa and other regions, often of Afrikaans or Chinese origin depending on cultural context.
  • A. Ruian
    Ruian is a county-level coastal city administered by Wenzhou in Zhejiang Province, China, known for its private entrepreneurship and light manufacturing industries.
  • B. Róng
    Róng is the endonym used by the Lepcha people to refer to their own language spoken primarily in parts of India, Bhutan, and Nepal.
  • C. Maonan
    The Maonan are a small ethnic minority group in southern China known for their distinct Kam–Sui language, traditional rice farming, and rich folk customs.
  • D. Zuoren
    Zuoren is the given name of Zhou Zuoren, a prominent 20th-century Chinese essayist, translator, and literary critic.
  • E. Rushan
    Rushan is a county-level coastal city in eastern Shandong Province, China, known for its fishing industry, beaches, and marine-based economy.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9615cf6f48190bd0983cf7465ab15 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687bbb408190b80da2d0310f82c5 completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f6695372688190b09a2bb2e58cb546 completed May 2, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_69f669fe4bc48190adba50ad58b10c45 completed May 2, 2026, 9:17 p.m.
Created at: April 9, 2026, 5:18 p.m.