Triple

T9248845
Position Surface form Disambiguated ID Type / Status
Subject Zhou Zuoren E222265 entity
Predicate employer P7 FINISHED
Object Peking University E50963 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: Peking University | Statement: [Zhou Zuoren, employer, Peking University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peking University
Context triple: [Zhou Zuoren, employer, Peking University]
  • A. Peking University chosen
    Peking University is a leading Chinese research university in Beijing, renowned for its academic excellence, historical significance, and global influence.
  • B. Tsinghua University
    Tsinghua University is a leading research-intensive university in Beijing, China, renowned for its strong engineering, science, and technology programs and its significant influence in Chinese higher education and innovation.
  • C. Renmin University of China
    Renmin University of China is a prestigious Beijing-based research university renowned for its strengths in the humanities and social sciences.
  • D. Beijing Normal University
    Beijing Normal University is a prestigious Chinese research university in Beijing, renowned for its strong programs in education and the humanities.
  • 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 (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_69ca841d2b18819089f9faf5b2c2aec0 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd05f6d62c8190a1e33f1854767b47 completed April 1, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69de54a30b748190bb791078e9dde442 completed April 14, 2026, 2:52 p.m.
Created at: March 30, 2026, 7:31 p.m.