Triple

T8919504
Position Surface form Disambiguated ID Type / Status
Subject C9 League E212375 entity
Predicate member P10 FINISHED
Object Nanjing University E170348 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: Nanjing University | Statement: [C9 League, member, Nanjing University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanjing University
Context triple: [C9 League, member, Nanjing University]
  • A. Nanjing University chosen
    Nanjing University is one of China’s oldest and most prestigious research universities, renowned for its strong academic programs and historical significance.
  • B. Soochow University
    Soochow University is a major comprehensive research university in Suzhou, China, known for its strong programs in humanities, social sciences, and engineering.
  • C. Nanjing Normal University
    Nanjing Normal University is a comprehensive public university in Nanjing, China, known for its strong teacher education programs and broad range of disciplines.
  • D. Peking University
    Peking University is a leading Chinese research university in Beijing, renowned for its academic excellence, historical significance, and global influence.
  • E. Fudan University
    Fudan University is a prestigious and comprehensive research university in Shanghai, China, renowned for its strong academic programs and leading role in Chinese higher education.
  • 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_69ca839481d48190b42b037e0d0f636c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6613639881909090d060f388a865 completed April 1, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e4d5f5008190a897b3b10b172592 completed April 5, 2026, 10:40 p.m.
Created at: March 30, 2026, 6:56 p.m.