Triple

T21652986
Position Surface form Disambiguated ID Type / Status
Subject Michaela E534386 entity
Predicate hasVariant P455 FINISHED
Object Michele (feminine)
Michele is a feminine given name, commonly used in English and French, that originates as a variant of the name Michaela.
E1495454 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: Michele (feminine) | Statement: [Michaela, hasVariant, Michele (feminine)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michele (feminine)
Context triple: [Michaela, hasVariant, Michele (feminine)]
  • A. Michela
    Michela is a given name, commonly used in Italian- and Portuguese-speaking countries as a feminine form of Michael.
  • B. Michaëlle
    Michaëlle is a feminine given name most notably borne by Michaëlle Jean, the former Governor General of Canada.
  • C. Chiara Lucia
    Chiara Lucia is a feminine given name, typically used in Italian-speaking contexts as a compound form of Chiara and Lucia.
  • D. Mishael
    Mishael is one of the three Hebrew youths in the biblical additions to Daniel who, along with his companions, is miraculously preserved in the fiery furnace.
  • E. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • 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: Michele (feminine)
Triple: [Michaela, hasVariant, Michele (feminine)]
Generated description
Michele is a feminine given name, commonly used in English and French, that originates as a variant of the name Michaela.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michele (feminine)
Target entity description: Michele is a feminine given name, commonly used in English and French, that originates as a variant of the name Michaela.
  • A. Michela
    Michela is a given name, commonly used in Italian- and Portuguese-speaking countries as a feminine form of Michael.
  • B. Michaëlle
    Michaëlle is a feminine given name most notably borne by Michaëlle Jean, the former Governor General of Canada.
  • C. Chiara Lucia
    Chiara Lucia is a feminine given name, typically used in Italian-speaking contexts as a compound form of Chiara and Lucia.
  • D. Mishael
    Mishael is one of the three Hebrew youths in the biblical additions to Daniel who, along with his companions, is miraculously preserved in the fiery furnace.
  • E. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • 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_69e0c466aec88190ba39c7543dbc8ba2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef591594a08190bf0ddd0a0c0922ba completed April 27, 2026, 12:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a15960e348190b944ee34d80cd8a8 completed May 17, 2026, 7:23 p.m.
NEDg Description generation batch_6a0a16c278188190855335930666cede completed May 17, 2026, 7:28 p.m.
NED2 Entity disambiguation (via description) batch_6a0a17a2c81481908e229ea58e61843e completed May 17, 2026, 7:31 p.m.
Created at: April 16, 2026, 6:36 p.m.