Triple

T963679
Position Surface form Disambiguated ID Type / Status
Subject Maud of Wales E20789 entity
Predicate givenName P17 FINISHED
Object Maud
Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
 E117170 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: Maud | Statement: [Maud of Wales, givenName, Maud]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maud
Context triple: [Maud of Wales, givenName, Maud]
  • A. Milbanke
    Milbanke is an English aristocratic family name historically associated with the wife of poet Lord Byron, Annabella Milbanke.
  • B. Henrietta
    Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
  • C. Helene
    Helene is the given name of Leni Riefenstahl, the controversial German filmmaker and actress known for her propaganda films during the Nazi era.
  • D. Agatha
    Agatha was an 11th-century noblewoman, likely of Eastern European or possibly Hungarian or Kievan Rus' origin, best known as the mother of Edgar the Ætheling and Saint Margaret of Scotland.
  • E. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • 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: Maud
Triple: [Maud of Wales, givenName, Maud]
Generated description
Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maud
Target entity description: Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
  • A. Milbanke
    Milbanke is an English aristocratic family name historically associated with the wife of poet Lord Byron, Annabella Milbanke.
  • B. Henrietta
    Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
  • C. Helene
    Helene is the given name of Leni Riefenstahl, the controversial German filmmaker and actress known for her propaganda films during the Nazi era.
  • D. Agatha
    Agatha was an 11th-century noblewoman, likely of Eastern European or possibly Hungarian or Kievan Rus' origin, best known as the mother of Edgar the Ætheling and Saint Margaret of Scotland.
  • E. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b416cf4c8190bd685227db25fb53 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac25845f588190b0f60754636a88d0 completed March 7, 2026, 1:17 p.m.
NEDg Description generation batch_69ac2674f5b88190bb3416a249a63982 completed March 7, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_69ac2704de788190857a3104180ccd21 completed March 7, 2026, 1:24 p.m.
Created at: March 1, 2026, 7:40 p.m.