Triple

T19858194
Position Surface form Disambiguated ID Type / Status
Subject John E477188 entity
Predicate hasFeminineForm P1613 FINISHED
Object Joanne 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: Joanne | Statement: [John, hasFeminineForm, Joanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joanne
Context triple: [John, hasFeminineForm, Joanne]
  • A. Joanne chosen
    Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
  • B. Joanne
    "Joanne" is a country- and rock-influenced studio album by American singer-songwriter Lady Gaga that explores themes of family, loss, and personal identity.
  • C. Joanie
    Joanie is a diminutive form of the given name Joan, often used as a familiar or affectionate nickname.
  • D. Joanna
    Joanna is a key character in the cult-classic comedy film "Office Space," known as the friendly waitress who becomes the love interest of the protagonist.
  • E. Joanna
    Joanna is a feminine given name used in various cultures, often associated with forms of the name John and shared by many notable historical and contemporary figures.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586dbbf0819089e7157d416aeaaf completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.