Triple

T12067571
Position Surface form Disambiguated ID Type / Status
Subject Waldeck-Pyrmont dynasty E287335 entity
Predicate hasNotableMember P304 FINISHED
Object Princess Louise of Waldeck and Pyrmont
Princess Louise of Waldeck and Pyrmont was a 19th-century German noblewoman and member of the House of Waldeck and Pyrmont who became notable through her dynastic connections within European aristocracy.
E1030601 NE FINISHED

How this triple was built (4 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: Princess Louise of Waldeck and Pyrmont | Statement: [Waldeck-Pyrmont dynasty, hasNotableMember, Princess Louise of Waldeck and Pyrmont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Princess Louise of Waldeck and Pyrmont
Context triple: [Waldeck-Pyrmont dynasty, hasNotableMember, Princess Louise of Waldeck and Pyrmont]
  • A. Princess Louise of Saxe-Gotha-Altenburg
    Princess Louise of Saxe-Gotha-Altenburg was a German duchess of the early 19th century, best known as the first wife of Ernest I, Duke of Saxe-Coburg and Gotha, and the mother of Prince Albert, consort of Queen Victoria.
  • B. Princess Louise of Saxe-Hildburghausen
    Princess Louise of Saxe-Hildburghausen was a German duchess of the House of Saxe-Hildburghausen and the mother of Adolphe, who became Grand Duke of Luxembourg.
  • C. Princess Louise Margaret of Prussia
    Princess Louise Margaret of Prussia was a German-born princess who became Duchess of Connaught and Strathearn through marriage into the British royal family and was the mother of Princess Margaret of Connaught.
  • D. Princess Louise of Prussia
    Princess Louise of Prussia was a 19th-century Prussian royal and member of the House of Hohenzollern who became a Dutch princess through her marriage into the Dutch royal family.
  • E. Princess Louise Caroline of Hesse-Kassel
    Princess Louise Caroline of Hesse-Kassel was a German-Danish noblewoman and duchess best known as the mother of Christian IX of Denmark, the “Father-in-law of Europe.”
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Princess Louise of Waldeck and Pyrmont
Triple: [Waldeck-Pyrmont dynasty, hasNotableMember, Princess Louise of Waldeck and Pyrmont]
Generated description
Princess Louise of Waldeck and Pyrmont was a 19th-century German noblewoman and member of the House of Waldeck and Pyrmont who became notable through her dynastic connections within European aristocracy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Princess Louise of Waldeck and Pyrmont
Target entity description: Princess Louise of Waldeck and Pyrmont was a 19th-century German noblewoman and member of the House of Waldeck and Pyrmont who became notable through her dynastic connections within European aristocracy.
  • A. Princess Louise of Saxe-Gotha-Altenburg
    Princess Louise of Saxe-Gotha-Altenburg was a German duchess of the early 19th century, best known as the first wife of Ernest I, Duke of Saxe-Coburg and Gotha, and the mother of Prince Albert, consort of Queen Victoria.
  • B. Princess Louise of Saxe-Hildburghausen
    Princess Louise of Saxe-Hildburghausen was a German duchess of the House of Saxe-Hildburghausen and the mother of Adolphe, who became Grand Duke of Luxembourg.
  • C. Princess Louise Margaret of Prussia
    Princess Louise Margaret of Prussia was a German-born princess who became Duchess of Connaught and Strathearn through marriage into the British royal family and was the mother of Princess Margaret of Connaught.
  • D. Princess Louise of Prussia
    Princess Louise of Prussia was a 19th-century Prussian royal and member of the House of Hohenzollern who became a Dutch princess through her marriage into the Dutch royal family.
  • E. Princess Louise Caroline of Hesse-Kassel
    Princess Louise Caroline of Hesse-Kassel was a German-Danish noblewoman and duchess best known as the mother of Christian IX of Denmark, the “Father-in-law of Europe.”
  • F. None of above. chosen

Provenance (5 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904423dc08190a47194422255c62e completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a114ccc81909bc428c40c01a461 completed May 3, 2026, 8:40 a.m.
NEDg Description generation batch_69f70b5dbcc4819081b5ba410e319eb7 completed May 3, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_69f70c4c6f908190b2ebc2a90b049e59 completed May 3, 2026, 8:50 a.m.
Created at: April 8, 2026, 9:48 p.m.