Triple

T3891833
Position Surface form Disambiguated ID Type / Status
Subject Luise Erhard E88078 entity
Predicate givenName P17 FINISHED
Object Luise E39188 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: Luise | Statement: [Luise Erhard, givenName, Luise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luise
Context triple: [Luise Erhard, givenName, Luise]
  • A. Luise chosen
    Luise is a given name, primarily used in German-speaking countries, that corresponds to the English and French name Louise.
  • B. Maria Christina
    Maria Christina, known as Princess Christina of the Netherlands, was a Dutch royal and youngest daughter of Queen Juliana and Prince Bernhard who became known for her work as a singer and music educator.
  • C. Therese of Saxe-Hildburghausen
    Therese of Saxe-Hildburghausen was a Bavarian queen consort whose marriage to Crown Prince Ludwig I of Bavaria is famously commemorated by the annual Oktoberfest in Munich.
  • D. Maria Antonia of Bavaria
    Maria Antonia of Bavaria was an 18th-century Bavarian princess of the Wittelsbach dynasty known for her role in European dynastic politics.
  • E. Maria of Simmern
    Maria of Simmern was a 16th-century German noblewoman and princess from the Palatine branch of the Wittelsbach dynasty.
  • 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecb237748190a4d41b76e8efd0ba completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576852d0c819083d377bab6799ec7 completed March 14, 2026, 2:53 p.m.
Created at: March 9, 2026, 3:21 p.m.