Triple

T4542251
Position Surface form Disambiguated ID Type / Status
Subject Aldous Huxley E107560 entity
Predicate spouse P13 FINISHED
Object Maria Nys E107560 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: Maria Nys | Statement: [Aldous Huxley, spouse, Maria Nys]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria Nys
Context triple: [Aldous Huxley, spouse, Maria Nys]
  • A. Maria Nys chosen
    Maria Nys was a Belgian-born woman best known as the first wife of English writer Aldous Huxley and a central figure in his personal and social life.
  • B. Sophie Wilmès
    Sophie Wilmès is a Belgian liberal politician who became the country’s first female prime minister, leading the federal government during the initial phase of the COVID-19 pandemic.
  • C. Celine Buckens
    Celine Buckens is a Belgian-born British actress best known for her breakout role in Steven Spielberg’s film "War Horse" and subsequent work in television dramas.
  • D. Maayke Velders
    Maayke Velders is known primarily as the spouse of Dutch naval hero Michiel de Ruyter.
  • E. Sara Catrijne van der Straten
    Sara Catrijne van der Straten was a 17th-century Dutch woman best known as the wife of admiral Cornelis Tromp, a prominent naval commander of the Dutch Republic.
  • 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_69bd43f922788190b7edfa294e39b178 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d3be988190bf118c4a87415613 completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc55ae8248190acda4f10eb5ce2e7 completed March 20, 2026, 10:08 p.m.
Created at: March 20, 2026, 1:04 p.m.