Triple

T9131709
Position Surface form Disambiguated ID Type / Status
Subject Mélanie Thierry E219101 entity
Predicate givenName P17 FINISHED
Object Mélanie
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
E782949 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: Mélanie | Statement: [Mélanie Thierry, givenName, Mélanie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mélanie
Context triple: [Mélanie Thierry, givenName, Mélanie]
  • A. Léa
    Léa is a French feminine given name commonly used in Francophone countries.
  • B. Stéphanie
    Stéphanie is a Monegasque princess, singer, and fashion designer, best known as the youngest child of Prince Rainier III and Grace Kelly.
  • C. Margot
    Margot is a feminine given name of French origin, often associated with Margot Frank, the elder sister of diarist Anne Frank.
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Sophie Dumond
    Sophie Dumond is Arthur Fleck’s single-mother neighbor and tentative love interest in the 2019 film "Joker," representing his yearning for connection and normalcy amid his psychological unraveling.
  • 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: Mélanie
Triple: [Mélanie Thierry, givenName, Mélanie]
Generated description
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mélanie
Target entity description: Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
  • A. Léa
    Léa is a French feminine given name commonly used in Francophone countries.
  • B. Stéphanie
    Stéphanie is a Monegasque princess, singer, and fashion designer, best known as the youngest child of Prince Rainier III and Grace Kelly.
  • C. Margot
    Margot is a feminine given name of French origin, often associated with Margot Frank, the elder sister of diarist Anne Frank.
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Sophie Dumond
    Sophie Dumond is Arthur Fleck’s single-mother neighbor and tentative love interest in the 2019 film "Joker," representing his yearning for connection and normalcy amid his psychological unraveling.
  • 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_69ca83debfc0819095800583e97ab10f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8ceea6c81909f368f12dac1649c completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0544f7be481908f247889363c0f32 completed April 3, 2026, 11:59 p.m.
NEDg Description generation batch_69d057ff4a7c819086213940563ef753 completed April 4, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_69d058cd8f2481908528e2862c91384b completed April 4, 2026, 12:18 a.m.
Created at: March 30, 2026, 7:18 p.m.