Triple

T15676502
Position Surface form Disambiguated ID Type / Status
Subject Lara Fabian E377456 entity
Predicate notableWork P4 FINISHED
Object Tout
"Tout" is a popular French-language ballad by Belgian-Canadian singer Lara Fabian that helped establish her international success in the late 1990s.
 E1171386 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: Tout | Statement: [Lara Fabian, notableWork, Tout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tout
Context triple: [Lara Fabian, notableWork, Tout]
  • A. Tout
    Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
  • B. Tous
    Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • C. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • D. Thourout
    Thourout is a town in West Flanders, Belgium, historically notable as the place where the French geographer and anarchist Élisée Reclus died.
  • E. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • 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: Tout
Triple: [Lara Fabian, notableWork, Tout]
Generated description
"Tout" is a popular French-language ballad by Belgian-Canadian singer Lara Fabian that helped establish her international success in the late 1990s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tout
Target entity description: "Tout" is a popular French-language ballad by Belgian-Canadian singer Lara Fabian that helped establish her international success in the late 1990s.
  • A. Tout
    Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
  • B. Tous
    Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • C. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • D. Thourout
    Thourout is a town in West Flanders, Belgium, historically notable as the place where the French geographer and anarchist Élisée Reclus died.
  • E. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2e10a4819097eba1ea31e36ac2 completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6edd85148190b6d5c3981204dd77 completed May 9, 2026, 5:29 p.m.
NEDg Description generation batch_69ff6fd9c968819098b2552a9deb0445 completed May 9, 2026, 5:33 p.m.
NED2 Entity disambiguation (via description) batch_69ff708d42448190a53b90e00721eaa5 completed May 9, 2026, 5:36 p.m.
Created at: April 10, 2026, 4:16 a.m.