Triple

T13857040
Position Surface form Disambiguated ID Type / Status
Subject CPGE E333092 entity
Predicate firstYearNickname P10581 FINISHED
Object hypokhâgne
Hypokhâgne is the first year of France’s selective humanities-focused preparatory classes for the competitive entrance exams to elite grandes écoles.
E1066931 NE FINISHED

How this triple was built (5 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: hypokhâgne | Statement: [CPGE, firstYearNickname, hypokhâgne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: hypokhâgne
Context triple: [CPGE, firstYearNickname, hypokhâgne]
  • A. Petite École
    Petite École was a French art school in Paris known for training young artists in drawing and decorative arts, attended by notable figures such as Auguste Rodin.
  • B. École
    École is a small French village located in the Massif des Bauges mountain range in southeastern France.
  • C. École de la Gradelle
    École de la Gradelle is a local primary school serving the community of Chêne-Bougeries in the canton of Geneva, Switzerland.
  • D. Gymnasium
    Gymnasium is a modern open-source toolkit for developing and comparing reinforcement learning algorithms, serving as a successor and refinement to OpenAI Gym.
  • E. La Maternelle
    La Maternelle is a French film in which actor Victor Francen delivered one of his most recognized performances.
  • 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: hypokhâgne
Triple: [CPGE, firstYearNickname, hypokhâgne]
Generated description
Hypokhâgne is the first year of France’s selective humanities-focused preparatory classes for the competitive entrance exams to elite grandes écoles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: hypokhâgne
Target entity description: Hypokhâgne is the first year of France’s selective humanities-focused preparatory classes for the competitive entrance exams to elite grandes écoles.
  • A. Petite École
    Petite École was a French art school in Paris known for training young artists in drawing and decorative arts, attended by notable figures such as Auguste Rodin.
  • B. École
    École is a small French village located in the Massif des Bauges mountain range in southeastern France.
  • C. École de la Gradelle
    École de la Gradelle is a local primary school serving the community of Chêne-Bougeries in the canton of Geneva, Switzerland.
  • D. Gymnasium
    Gymnasium is a modern open-source toolkit for developing and comparing reinforcement learning algorithms, serving as a successor and refinement to OpenAI Gym.
  • E. La Maternelle
    La Maternelle is a French film in which actor Victor Francen delivered one of his most recognized performances.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: firstYearNickname
Context triple: [CPGE, firstYearNickname, hypokhâgne]
  • A. childhoodNickname
    Indicates that one entity is a nickname that was used to refer to the other entity during their childhood.
  • B. firstYear
    Indicates that an entity is in its first year of existence, operation, or participation within a specified context.
  • C. nicknameOfYear chosen
    Indicates that a given nickname is used to refer to or characterize a particular year.
  • D. academyNickname
    Indicates that an entity is known by a particular informal or colloquial nickname within an academy or academic institution context.
  • E. unofficialNickname
    Indicates that one entity is informally or colloquially known by a non-official nickname represented by the other entity.
  • F. None of above.

Provenance (6 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02dc9f488190b7181dcb7e304632 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0fb7c3c819081fc6f89aa17d6af completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c2c711948190ac614291592a7e03 completed May 3, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69f7c36f28b48190b734a9e5e7ae39b9 completed May 3, 2026, 9:51 p.m.
PD Predicate disambiguation batch_69dbc8691b608190a25a7c70a366b170 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:14 p.m.