Triple

T16474452
Position Surface form Disambiguated ID Type / Status
Subject Fanny Shaw E400150 entity
Predicate hasGivenName P17 FINISHED
Object Fanny E287859 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: Fanny | Statement: [Fanny Shaw, hasGivenName, Fanny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fanny
Context triple: [Fanny Shaw, hasGivenName, Fanny]
  • A. Fanny
    Fanny is one of the central child protagonists in Enid Blyton’s classic fantasy series "The Magic Faraway Tree," known for her adventurous spirit and explorations of the magical lands at the top of the tree.
  • B. Fanny chosen
    Fanny is a feminine given name commonly used in various European and English-speaking countries.
  • C. Fanny
    Fanny is a central character in the Swedish dark comedy-drama film "Force Majeure," which explores family dynamics and moral dilemmas during a ski vacation in the French Alps.
  • D. Fanny
    Fanny is a 1961 romantic drama film adaptation of Marcel Pagnol’s works, best known for starring French actress Leslie Caron.
  • E. Fanny Harker
    Fanny Harker is a notable individual who shares the surname Harker, recognized enough to be specifically identified among bearers of the name.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32dd32e048190a9eadd32d6b9374c completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f5f238881909b5f2fb41da3f932 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:13 a.m.