Triple

T15601133
Position Surface form Disambiguated ID Type / Status
Subject China University of Political Science and Law E375034 entity
Predicate abbreviation P43 FINISHED
Object CUPL
CUPL is a leading Chinese university specializing in law and political science, renowned for its influential role in legal education and research in China.
 E1167377 NE FINISHED

How this triple was built (4 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: CUPL | Statement: [China University of Political Science and Law, abbreviation, CUPL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CUPL
Context triple: [China University of Political Science and Law, abbreviation, CUPL]
  • A. CUC
    CUC is the national organization representing Unitarian and Unitarian Universalist congregations across Canada, providing support, resources, and coordination for their religious and social justice activities.
  • B. CuSP
    CuSP is a small CubeSat spacecraft designed to study space weather and the interplanetary environment.
  • C. CUA
    CUA is a joint MIT–Harvard research center focused on the study of ultracold atomic physics and quantum phenomena.
  • D. CUA
    CUA is the ICAO airline designator for China United Airlines, a Chinese domestic carrier based in Beijing.
  • E. CUCS
    CUCS is a health sciences university center of the University of Guadalajara in Mexico, focused on education and research in medical and related disciplines.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: CUPL
Triple: [China University of Political Science and Law, abbreviation, CUPL]
Generated description
CUPL is a leading Chinese university specializing in law and political science, renowned for its influential role in legal education and research in China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CUPL
Target entity description: CUPL is a leading Chinese university specializing in law and political science, renowned for its influential role in legal education and research in China.
  • A. CUC
    CUC is the national organization representing Unitarian and Unitarian Universalist congregations across Canada, providing support, resources, and coordination for their religious and social justice activities.
  • B. CuSP
    CuSP is a small CubeSat spacecraft designed to study space weather and the interplanetary environment.
  • C. CUA
    CUA is a joint MIT–Harvard research center focused on the study of ultracold atomic physics and quantum phenomena.
  • D. CUA
    CUA is the ICAO airline designator for China United Airlines, a Chinese domestic carrier based in Beijing.
  • E. CUCS
    CUCS is a health sciences university center of the University of Guadalajara in Mexico, focused on education and research in medical and related disciplines.
  • F. None of above. chosen

Provenance (5 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e621fc4819097e8e85e7ddfdc6c completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56cf8e5c8190bf13114ab0a834de completed May 9, 2026, 3:46 p.m.
NEDg Description generation batch_69ff5acd35648190a204b78f7fb9619c completed May 9, 2026, 4:03 p.m.
NED2 Entity disambiguation (via description) batch_69ff5b3f71148190a96c6f396512c1fd completed May 9, 2026, 4:05 p.m.
Created at: April 10, 2026, 4:12 a.m.