Triple

T2417240
Position Surface form Disambiguated ID Type / Status
Subject École Centrale des Arts et Manufactures E52333 entity
Predicate shortName P43 FINISHED
Object Centrale
Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
 E265431 NE FINISHED

How this triple was built (4 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: Centrale | Statement: [École Centrale des Arts et Manufactures, shortName, Centrale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Centrale
Context triple: [École Centrale des Arts et Manufactures, shortName, Centrale]
  • A. Centrs
    Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
  • B. Sentrum
    Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
  • C. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • D. Cité
    Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
  • E. Corine
    Corine is a feminine given name used in various European countries, often considered a variant of "Corinne."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Centrale
Triple: [École Centrale des Arts et Manufactures, shortName, Centrale]
Generated description
Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Centrale
Target entity description: Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
  • A. Centrs
    Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
  • B. Sentrum
    Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
  • C. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • D. Cité
    Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
  • E. Corine
    Corine is a feminine given name used in various European countries, often considered a variant of "Corinne."
  • F. None of above. chosen

Provenance (5 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc94eafd481909eeff689e5bf5960 completed March 7, 2026, 6:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf4dcf6c8190a51f26af7e7a9b9c completed March 9, 2026, 12:38 p.m.
NEDg Description generation batch_69aec2b3291c8190966344cd20963660 completed March 9, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_69aec30f9ef481909b83f3cf9fd6e998 completed March 9, 2026, 12:54 p.m.
Created at: March 6, 2026, 9:42 p.m.