Triple

T4059396
Position Surface form Disambiguated ID Type / Status
Subject Ella E84771 entity
Predicate derivedFrom P909 FINISHED
Object Eleanor E5505 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: Eleanor | Statement: [Ella, derivedFrom, Eleanor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eleanor
Context triple: [Ella, derivedFrom, Eleanor]
  • A. Eleanor chosen
    Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
  • B. Eleanor
    Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
  • C. Katherine
    Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
  • D. Isabella
    Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
  • E. Isabella
    Isabella is the given name of Mrs Beeton, the famed 19th-century English author of the influential household management guide "Mrs Beeton's Book of Household Management."
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd13b4481908f9c09cc4f4a9724 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a98c488190a7e77cd46ff998bc completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:38 p.m.