Triple

T1275940
Position Surface form Disambiguated ID Type / Status
Subject Alizée E27213 entity
Predicate givenName P17 FINISHED
Object Alizée E27213 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: Alizée | Statement: [Alizée, givenName, Alizée]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alizée
Context triple: [Alizée, givenName, Alizée]
  • A. Alizée chosen
    Alizée is a French pop singer and dancer who rose to international fame in the early 2000s with her hit single "Moi... Lolita."
  • B. Mireille Mathieu
    Mireille Mathieu is a French chanteuse renowned for her powerful voice, classic chanson repertoire, and international success since the 1960s.
  • C. Elissa
    Elissa, also known as Dido, is the legendary Phoenician princess who founded the ancient city of Carthage and became its first queen.
  • D. Patricia Kaas
    Patricia Kaas is a French singer and actress known for her distinctive husky voice and modern take on classic chanson, blending pop, jazz, and cabaret influences.
  • E. Surya Bonaly
    Surya Bonaly is a French figure skater renowned for her powerful athleticism, multiple European titles, and for performing a historic backflip on one blade in Olympic competition.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c08ef32c8190a493c8215946e5dd completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb2fd091081908f4a60d7ce300c90 completed March 7, 2026, 11:21 p.m.
Created at: March 1, 2026, 7:50 p.m.