Triple

T3242487
Position Surface form Disambiguated ID Type / Status
Subject National Technical University of Athens E67992 entity
Predicate affiliation 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: [National Technical University of Athens, affiliation, CESAER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CESAER
Context triple: [National Technical University of Athens, affiliation, 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf17463481909447f6ab46016407 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b27757dff0819081a26aea52ede49d completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.