Triple

T21382209
Position Surface form Disambiguated ID Type / Status
Subject Guo Shuqing E527386 entity
Predicate education P5 FINISHED
Object Nankai University NE NERFINISHED

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: Nankai University | Statement: [Guo Shuqing, education, Nankai University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nankai University
Context triple: [Guo Shuqing, education, Nankai University]
  • A. Nankai University chosen
    Nankai University is a prestigious public research university in Tianjin, China, renowned for its strong programs in the sciences, economics, and humanities.
  • B. Osaka Imperial University
    Osaka Imperial University was a major pre-World War II Japanese national university and research institution, particularly noted for its contributions to science and engineering.
  • C. Soochow University
    Soochow University is a major comprehensive research university in Suzhou, China, known for its strong programs in humanities, social sciences, and engineering.
  • D. National Chekiang University
    National Chekiang University was a prominent pre-1949 Chinese higher education institution that later evolved into the modern Zhejiang University.
  • E. Nanjing University
    Nanjing University is one of China’s oldest and most prestigious research universities, renowned for its strong academic programs and historical significance.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0d1fa1c8190b3374e0bb3a971fc completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:12 p.m.