Triple

T18949160
Position Surface form Disambiguated ID Type / Status
Subject Shenzhen University E463597 entity
Predicate hasFaculty P141 FINISHED
Object College of Foreign Languages NE NERFINISHED

How this triple was built (3 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: College of Foreign Languages | Statement: [Shenzhen University, hasFaculty, College of Foreign Languages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College of Foreign Languages
Context triple: [Shenzhen University, hasFaculty, College of Foreign Languages]
  • A. College of Foreign Languages
    The College of Foreign Languages at Nankai University is an academic faculty specializing in the teaching and research of multiple foreign languages, literatures, and related cultural studies.
  • B. College of Foreign Languages
    The College of Foreign Languages is an academic unit of Hunan Normal University specializing in the teaching and research of foreign languages and related disciplines.
  • C. College of Foreign Languages and Cultures
    The College of Foreign Languages and Cultures is an academic unit of the University of Tartu specializing in the study and teaching of foreign languages, literatures, and related cultural studies.
  • D. College of Foreign Languages and Cultures
    The College of Foreign Languages and Cultures is an academic unit of Xiamen University specializing in foreign language education, literature, and cross-cultural studies.
  • E. School of Foreign Languages
    The School of Foreign Languages at Tongji University is an academic unit specializing in language education, linguistics, and intercultural studies within the university.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: College of Foreign Languages
Target entity description: The College of Foreign Languages is an academic unit of Shenzhen University specializing in the teaching and research of foreign languages and related disciplines.
  • A. College of Foreign Languages
    The College of Foreign Languages at Nankai University is an academic faculty specializing in the teaching and research of multiple foreign languages, literatures, and related cultural studies.
  • B. College of Foreign Languages
    The College of Foreign Languages is an academic unit of Hunan Normal University specializing in the teaching and research of foreign languages and related disciplines.
  • C. College of Foreign Languages and Cultures
    The College of Foreign Languages and Cultures is an academic unit of the University of Tartu specializing in the study and teaching of foreign languages, literatures, and related cultural studies.
  • D. College of Foreign Languages and Cultures
    The College of Foreign Languages and Cultures is an academic unit of Xiamen University specializing in foreign language education, literature, and cross-cultural studies.
  • E. School of Foreign Languages
    The School of Foreign Languages at Tongji University is an academic unit specializing in language education, linguistics, and intercultural studies within the university.
  • F. None of above. chosen

Provenance (2 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_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d541ef18819080b2e253dd23835d completed April 20, 2026, 7:26 a.m.
Created at: April 10, 2026, noon