Triple

T13070738
Position Surface form Disambiguated ID Type / Status
Subject ENSTA Paris E329448 entity
Predicate acronym P43 FINISHED
Object ENSTA E329448 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: ENSTA | Statement: [ENSTA Paris, acronym, ENSTA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ENSTA
Context triple: [ENSTA Paris, acronym, ENSTA]
  • A. ENSTA Group
    ENSTA Group is a French network of elite engineering schools specializing in advanced science and technology education and research.
  • B. ENSTA Paris chosen
    ENSTA Paris is a leading French grande école of engineering and research, specializing in advanced science and technology, and is one of the founding schools of the Institut Polytechnique de Paris.
  • C. ENSTA Bretagne
    ENSTA Bretagne is a leading French engineering grande école and research institution specializing in naval, defense, and high-technology fields, located in Brest.
  • D. ENAC
    ENAC is the School of Architecture, Civil and Environmental Engineering at EPFL in Switzerland, encompassing education and research in the built and natural environment.
  • E. Crystal Palace School of Engineering
    Crystal Palace School of Engineering was a British technical institution known for training early 20th-century engineers, including aviation pioneer Geoffrey de Havilland.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ee6130819095d835e7ff6a8c5b completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d60510dc81909e0cba8b63a50d9c completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 9 p.m.