Triple

T5385623
Position Surface form Disambiguated ID Type / Status
Subject Tus E120194 entity
Predicate hasAlternativeName P39 FINISHED
Object Tous
Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
 E515458 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: Tous | Statement: [Tus, hasAlternativeName, Tous]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tous
Context triple: [Tus, hasAlternativeName, Tous]
  • A. Barcha
    Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
  • B. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • C. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • D. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • E. Yalli
    Yalli is a traditional Azerbaijani group folk dance characterized by dancers holding hands or shoulders and moving in synchronized circular or linear formations.
  • 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: Tous
Triple: [Tus, hasAlternativeName, Tous]
Generated description
Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tous
Target entity description: Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • A. Barcha
    Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
  • B. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • C. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • D. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • E. Yalli
    Yalli is a traditional Azerbaijani group folk dance characterized by dancers holding hands or shoulders and moving in synchronized circular or linear formations.
  • 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_69bd46354c648190a38b26f107010a96 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd86f5a7388190aa4ba2052afca74e completed March 20, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf295352988190a48d3f9db56fcaf8 completed March 21, 2026, 11:27 p.m.
NEDg Description generation batch_69bf29f4c56481908d3f83ec6e7ba96a completed March 21, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_69bf2ab19a50819098ef5a611daa8cd6 completed March 21, 2026, 11:33 p.m.
Created at: March 20, 2026, 2:03 p.m.