Triple

T5564168
Position Surface form Disambiguated ID Type / Status
Subject Moi... Lolita E145839 entity
Predicate writer P1360 FINISHED
Object Mylène Farmer E150582 NE FINISHED

How this triple was built (2 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: Mylène Farmer | Statement: [Moi... Lolita, writer, Mylène Farmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mylène Farmer
Context triple: [Moi... Lolita, writer, Mylène Farmer]
  • A. Mylène Farmer chosen
    Mylène Farmer is a French singer-songwriter and producer renowned for her melancholic pop music, poetic lyrics, and visually striking, often controversial music videos.
  • B. Mireille Mathieu
    Mireille Mathieu is a French chanteuse renowned for her powerful voice, classic chanson repertoire, and international success since the 1960s.
  • C. Nelly Roussel
    Nelly Roussel was a pioneering French feminist, neo-Malthusian activist, and orator known for her advocacy of birth control, women’s rights, and social reform in the early 20th century.
  • D. Alizée
    Alizée is a French pop singer and dancer who rose to international fame in the early 2000s with her hit single "Moi... Lolita."
  • E. Nancy Marchand
    Nancy Marchand was an acclaimed American actress best known for her roles on the television series "Lou Grant" and "The Sopranos."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008fdae24819081aa002ad99cd966 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02032330c819094f2bc1e8c93a5b6 completed March 22, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d0ca0088190a5d63139ba194e8e completed March 22, 2026, 8:11 p.m.
Created at: March 22, 2026, 3:36 p.m.