Triple

T23188372
Position Surface form Disambiguated ID Type / Status
Subject Nanette Newman E579660 entity
Predicate givenName P17 FINISHED
Object Nanette NE NERFINISHED

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: Nanette | Statement: [Nanette Newman, givenName, Nanette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanette
Context triple: [Nanette Newman, givenName, Nanette]
  • A. Nanette chosen
    Nanette is a feminine given name of French origin, commonly used in English- and French-speaking countries.
  • B. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • C. Yente
    Yente is the village matchmaker in the musical "Fiddler on the Roof," known for her gossiping and meddling in the romantic lives of Anatevka’s residents.
  • D. Ninette
    Ninette is a middle name of Countess Emma Luana of Orange-Nassau, a member of the Dutch royal family.
  • E. Pasqualina
    Pasqualina is an Italian feminine given name, traditionally associated with the Easter period and used in various regions of Italy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245ff8000819090d12008805315b7 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18fd592248190a7e705c554885cd1 completed April 29, 2026, 4:57 a.m.
Created at: April 17, 2026, 4:05 p.m.