Triple

T10441294
Position Surface form Disambiguated ID Type / Status
Subject Shanghai University of Finance and Economics E246175 entity
Predicate shortName P43 FINISHED
Object SUFE E766502 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: SUFE | Statement: [Shanghai University of Finance and Economics, shortName, SUFE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SUFE
Context triple: [Shanghai University of Finance and Economics, shortName, SUFE]
  • A. SWUFE chosen
    SWUFE is a leading Chinese university specializing in finance, economics, and business education and research.
  • B. SCUT
    SCUT is a major public research university in Guangzhou, China, known for its strong engineering, technology, and applied science programs.
  • C. Central South University
    Central South University is a major comprehensive research university in Changsha, Hunan, China, known for its strong engineering, medical, and materials science programs.
  • D. NUAA
    NUAA is a leading Chinese university in Nanjing specializing in aeronautics, astronautics, and engineering disciplines.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fb9ebf488190ae776bd65e94cb00 completed April 7, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87ed6edd88190afd5063daba58a46 completed April 10, 2026, 4:38 a.m.
Created at: April 6, 2026, 12:15 p.m.