Triple

T12054765
Position Surface form Disambiguated ID Type / Status
Subject 南开大学 E287010 entity
Predicate 中文名 P4878 FINISHED
Object 南开大学 E287010 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: 南开大学 | Statement: [南开大学, 中文名, 南开大学]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 南开大学
Context triple: [南开大学, 中文名, 南开大学]
  • A. 南开大学 chosen
    南开大学 is a prestigious comprehensive research university in Tianjin, China, renowned for its strong academic tradition and influential alumni.
  • B. 東北大学
    東北大学は、日本の宮城県仙台市に本部を置く、研究力と工学・理学分野で特に高い評価を受ける国立総合大学です。
  • C. 西南大学
    西南大学 is a comprehensive national university in Chongqing, China, known for its strengths in teacher education, agriculture, and the humanities and social sciences.
  • D. Peking University
    Peking University is a leading Chinese research university in Beijing, renowned for its academic excellence, historical significance, and global influence.
  • E. Tianjin Beiyang School of Law and Politics
    Tianjin Beiyang School of Law and Politics was an early modern Chinese institution of higher education specializing in legal and political studies that trained influential figures in China’s revolutionary and intellectual history.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90425258c8190ba7b3b837c439253 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49dea043c8190a74ffb448bbae5d0 completed May 1, 2026, 12:34 p.m.
Created at: April 8, 2026, 9:47 p.m.