Triple

T4335628
Position Surface form Disambiguated ID Type / Status
Subject Aletta Jacobs E97455 entity
Predicate givenName P17 FINISHED
Object Aletta E360042 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: Aletta | Statement: [Aletta Jacobs, givenName, Aletta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aletta
Context triple: [Aletta Jacobs, givenName, Aletta]
  • A. Wilhelmina
    Wilhelmina was a Prussian princess of the House of Hohenzollern who became Princess of Orange through marriage and played a significant political role in the Dutch Republic in the late 18th century.
  • B. Madalena
    Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • C. Madalena
    Madalena is a coastal town on the Azorean island of Pico in Portugal, known as a gateway to Mount Pico and for its wine culture and maritime heritage.
  • D. Hendrika chosen
    Hendrika is a feminine given name of Dutch origin, commonly used in the Netherlands and related to the name Hendrickje.
  • E. Emily Damstra
    Emily Damstra is a Canadian-born scientific illustrator and coin designer known for her detailed nature-themed artwork for the U.S. Mint and other institutions.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35152bfc88190ab5d53ca38f98d8a completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0a9967481908828ceeb76ce4cbf completed March 14, 2026, 9:18 p.m.
Created at: March 12, 2026, 11:14 p.m.