Triple

T11770423
Position Surface form Disambiguated ID Type / Status
Subject Hachette Livre E279881 entity
Predicate subsidiary P258 FINISHED
Object Hatier
Hatier is a French publishing house best known for its educational textbooks and study guides used widely in schools.
 E945727 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: Hatier | Statement: [Hachette Livre, subsidiary, Hatier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hatier
Context triple: [Hachette Livre, subsidiary, Hatier]
  • A. Guisa
    Guisa is a municipality and town located in Cuba’s eastern Granma Province, known for its rural character and historical significance in the Cuban Revolution.
  • B. Bachué
    Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
  • C. Harrie
    Harrie is a given name, typically a variant spelling of Harry, used for both males and females in various countries.
  • D. Hagaz
    Hagaz is a town in Eritrea’s Anseba region, known primarily as an agricultural and local administrative center.
  • E. Chaloub
    Chaloub is a surname of likely Arabic origin, used as a transliteration variant of the name Chalhub.
  • 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: Hatier
Triple: [Hachette Livre, subsidiary, Hatier]
Generated description
Hatier is a French publishing house best known for its educational textbooks and study guides used widely in schools.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hatier
Target entity description: Hatier is a French publishing house best known for its educational textbooks and study guides used widely in schools.
  • A. Guisa
    Guisa is a municipality and town located in Cuba’s eastern Granma Province, known for its rural character and historical significance in the Cuban Revolution.
  • B. Bachué
    Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
  • C. Harrie
    Harrie is a given name, typically a variant spelling of Harry, used for both males and females in various countries.
  • D. Hagaz
    Hagaz is a town in Eritrea’s Anseba region, known primarily as an agricultural and local administrative center.
  • E. Chaloub
    Chaloub is a surname of likely Arabic origin, used as a transliteration variant of the name Chalhub.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a55c9f988190b203b66a28c767ae completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f09086c4ec81908bc8b707a49c3ac2 completed April 28, 2026, 10:48 a.m.
NEDg Description generation batch_69f0bd3cf8308190813003daa8cfba4a completed April 28, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69f0ef02c930819086d139834ad4ed84 completed April 28, 2026, 5:31 p.m.
Created at: April 8, 2026, 9:41 p.m.