Triple

T10380228
Position Surface form Disambiguated ID Type / Status
Subject Ma Xiangbo E244619 entity
Predicate name P16 FINISHED
Object Ma Xiangbo E244619 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: Ma Xiangbo | Statement: [Ma Xiangbo, name, Ma Xiangbo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ma Xiangbo
Context triple: [Ma Xiangbo, name, Ma Xiangbo]
  • A. Ma Xiangbo chosen
    Ma Xiangbo was a prominent Chinese Jesuit priest, educator, and scholar who played a key role in modern Chinese higher education and founded several influential universities.
  • B. He Mengxiong
    He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
  • C. Liao Yaoxiang
    Liao Yaoxiang was a Nationalist Chinese general best known for commanding Kuomintang forces in major campaigns of the Chinese Civil War, including the Liaoshen Campaign.
  • D. Jiang Mianheng
    Jiang Mianheng is a Chinese physicist, businessman, and the son of former Chinese president Jiang Zemin, known for his influential roles in China's technology and telecommunications sectors.
  • E. Bao Xinhe
    Bao Xinhe is a Chinese physical chemist and academic leader known for his research in catalysis and for serving as president of the University of Science and Technology of China.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e991056c8190a981f717c51f1f72 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7b89a808190af9b2d4f37ad9012 completed April 18, 2026, 6:04 p.m.
Created at: April 6, 2026, 12:03 p.m.