Triple

T5205353
Position Surface form Disambiguated ID Type / Status
Subject HEC Paris E117497 entity
Predicate memberOf P10 FINISHED
Object EFMD E81770 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: EFMD | Statement: [HEC Paris, memberOf, EFMD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EFMD
Context triple: [HEC Paris, memberOf, EFMD]
  • A. EFMD chosen
    EFMD is a global, non-profit management development organization best known for accrediting business schools and programs worldwide.
  • B. EQUIS
    EQUIS is an international quality accreditation system for business and management schools, awarded by the European Foundation for Management Development (EFMD).
  • C. European Management Forum
    The European Management Forum was the original name of the organization that evolved into the World Economic Forum, an international institution best known for its annual meetings of global leaders in Davos, Switzerland.
  • D. SKEMA Business School
    SKEMA Business School is a leading French grande école and international business school known for its global campuses and strong focus on innovation, management, and digital transformation.
  • E. Bologna Process
    The Bologna Process is a European higher education reform initiative aimed at creating a more compatible, comparable, and coherent system of university degrees across participating countries.
  • 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_69bd4463dd3c81909966123f20b79d57 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a490338819080481df79d3aae01 completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefca8a1c81908eec1baa65bb06a3 completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:47 p.m.