Triple

T9876250
Position Surface form Disambiguated ID Type / Status
Subject Masaryk University E240079 entity
Predicate memberOf P10 FINISHED
Object CEEPUS E165644 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: CEEPUS | Statement: [Masaryk University, memberOf, CEEPUS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CEEPUS
Context triple: [Masaryk University, memberOf, CEEPUS]
  • A. CEEPUS chosen
    CEEPUS (Central European Exchange Program for University Studies) is a multilateral academic mobility and cooperation program that supports student and teacher exchanges among universities in Central and Eastern Europe.
  • B. CEPE
    CEPE is the commonly used abbreviation for the Community of Protestant Churches in Europe, a fellowship of Protestant churches across the continent.
  • C. CEPES
    CEPES is a regional center of UNESCO focused on higher education in Europe, promoting policy development, research, and international cooperation in the sector.
  • D. CEAS
    CEAS is the commonly used acronym for the College of Education and Allied Studies, an academic unit focused on preparing professionals in teaching, counseling, and related educational fields.
  • E. CEI
    CEI (Compagnie de l’Esthétique Industrielle) is a French industrial design company known for its work in product aesthetics and functional design across various industries.
  • 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3fb58d481908407898912c4b4e9 completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e47b62388190a033743376500375 completed April 5, 2026, 4:26 a.m.
Created at: March 30, 2026, 8:37 p.m.