Triple

T14556167
Position Surface form Disambiguated ID Type / Status
Subject INSA Rennes E341547 entity
Predicate shortName P43 FINISHED
Object INSA Rennes E341547 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: INSA Rennes | Statement: [INSA Rennes, shortName, INSA Rennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: INSA Rennes
Context triple: [INSA Rennes, shortName, INSA Rennes]
  • A. INSA Rennes chosen
    INSA Rennes is a leading French public engineering school located in Rennes, specializing in science and technology education and research.
  • B. INSA Lyon
    INSA Lyon is a leading French grande école and engineering school located near Lyon, renowned for its strong research activity and multidisciplinary engineering programs.
  • C. INSA Rouen Normandie
    INSA Rouen Normandie is a French grande école of engineering that offers multidisciplinary engineering education and research programs as part of the national INSA network.
  • D. Rennes 2 University
    Rennes 2 University is a French public university in Rennes specializing in the arts, humanities, social sciences, and sports sciences.
  • E. École Normale Supérieure de Rennes
    École Normale Supérieure de Rennes is a prestigious French grande école specializing in training high-level researchers, academics, and professionals in science, engineering, and social sciences.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f1490881908673f429e5288c86 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8abde0308190819da6867e703ea7 completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.