Triple

T9670678
Position Surface form Disambiguated ID Type / Status
Subject Armide E234017 entity
Predicate character P662 FINISHED
Object Sidonie
Sidonie is a character in Jean-Baptiste Lully’s opera *Armide*, typically portrayed as one of Armide’s attendants or confidantes within the enchanted realm.
 E813284 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: Sidonie | Statement: [Armide, character, Sidonie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sidonie
Context triple: [Armide, character, Sidonie]
  • A. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • B. Ursule
    Ursule is an alias used for the character Cosette in Victor Hugo’s novel "Les Misérables."
  • C. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • D. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • E. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • 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: Sidonie
Triple: [Armide, character, Sidonie]
Generated description
Sidonie is a character in Jean-Baptiste Lully’s opera *Armide*, typically portrayed as one of Armide’s attendants or confidantes within the enchanted realm.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sidonie
Target entity description: Sidonie is a character in Jean-Baptiste Lully’s opera *Armide*, typically portrayed as one of Armide’s attendants or confidantes within the enchanted realm.
  • A. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • B. Ursule
    Ursule is an alias used for the character Cosette in Victor Hugo’s novel "Les Misérables."
  • C. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • D. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • E. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • 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_69ca848f55e48190b3f67252571c3d45 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c3ec17081908c2da74a1d1f49da completed April 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a247ca48190910624dfbf0b491d completed April 4, 2026, 10:01 p.m.
NEDg Description generation batch_69d18acf86588190bc000f701bcaaa1c completed April 4, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69d18ba396cc8190a3ded2ac3968c553 completed April 4, 2026, 10:07 p.m.
Created at: March 30, 2026, 8:15 p.m.