Triple

T8376407
Position Surface form Disambiguated ID Type / Status
Subject Linda Chávez E197586 entity
Predicate givenName P17 FINISHED
Object Linda E28018 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: Linda | Statement: [Linda Chávez, givenName, Linda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linda
Context triple: [Linda Chávez, givenName, Linda]
  • A. Linda chosen
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • B. Linda
    Linda is a supporting character in the film "The Pursuit of Happyness," depicted as Chris Gardner’s struggling and increasingly distant partner amid the family’s financial hardships.
  • C. Linda
    Linda is a tragic, outcast figure in Aldous Huxley’s dystopian novel "Brave New World," whose experiences highlight the clash between the World State’s values and natural human emotion.
  • D. Laurie
    Laurie is a character from the horror film "Night Monster," involved in the eerie and suspenseful events surrounding the mysterious killings at the Ingston estate.
  • E. Laurie
    Laurie is a charming, wealthy, and impulsive young man who becomes a close friend and would-be suitor to the March sisters in Louisa May Alcott’s novel "Little Women."
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c094908190afe9cc54ce4f4d58 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce3967fd108190b045ea1328b1dc4b completed April 2, 2026, 9:39 a.m.
Created at: March 30, 2026, 6:01 p.m.