Triple

T3569709
Position Surface form Disambiguated ID Type / Status
Subject Polytechnic University of Turin E75537 entity
Predicate memberOf P10 FINISHED
Object CESAER E28802 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: CESAER | Statement: [Polytechnic University of Turin, memberOf, CESAER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CESAER
Context triple: [Polytechnic University of Turin, memberOf, CESAER]
  • A. CESAER chosen
    CESAER is a European association of leading universities of science and technology that collaborates to advance engineering education, research, and innovation.
  • B. CESA
    CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
  • C. Cellese
    Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
  • D. CESE
    CESE is France’s Economic, Social and Environmental Council, a constitutional advisory body that represents civil society and provides expert opinions on public policy.
  • E. CEA
    CEA is the abbreviation for China Eastern Airlines, one of China's major state-owned carriers operating extensive domestic and international flight networks.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0c1ecb081909051bcc1f38eea31 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbb3383c8190b14845a7de162502 completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:21 p.m.