Triple

T2086265
Position Surface form Disambiguated ID Type / Status
Subject Fannie E45356 entity
Predicate hasVariant P455 FINISHED
Object Frannie E219548 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: Frannie | Statement: [Fannie, hasVariant, Frannie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frannie
Context triple: [Fannie, hasVariant, Frannie]
  • A. Franny
    Franny is a common diminutive or nickname for the given name Frances.
  • B. Frannie Goldsmith chosen
    Frannie Goldsmith is a central protagonist in Stephen King’s post-apocalyptic novel "The Stand," known for her resilience, moral strength, and role in humanity’s struggle to rebuild after a devastating plague.
  • C. Valerie
    "Valerie" is a 1957 American Western film starring Sterling Hayden, loosely inspired by the Rashomon-style multiple-perspective narrative.
  • D. Clemmie
    Clemmie is a diminutive given name commonly used as a nickname for Clementine.
  • E. Trudy
    Trudy is the nickname of Gertrude Ederle, the American competitive swimmer who became the first woman to swim across the English Channel.
  • 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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba54ec048190bfe378aef1cc8086 completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae273f8e3481908c45f1686072a95d completed March 9, 2026, 1:49 a.m.
Created at: March 4, 2026, 7:41 p.m.