Triple

T6945263
Position Surface form Disambiguated ID Type / Status
Subject Johanna Maria Ruyter E160781 entity
Predicate givenName P17 FINISHED
Object Maria
Maria is a feminine given name of Latin origin, widely used across many cultures and often associated with Christian traditions.
 E103006 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: Maria | Statement: [Johanna Maria Ruyter, givenName, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maria
Context triple: [Johanna Maria Ruyter, givenName, Maria]
  • A. Maria
    Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
  • B. Maria
    Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
  • C. Maria
    Maria I of Portugal was the first queen regnant of Portugal, known for her devout Catholicism, initial period of enlightened reforms, and later mental illness that led to her son acting as regent.
  • D. Maria
    Maria is a witty and sharp-tongued lady-in-waiting to the Princess of France in William Shakespeare’s comedy "Love's Labour's Lost."
  • E. Maria
    Maria is a coastal municipality on Siquijor Island in the Philippines known for its rural communities and scenic seaside landscapes.
  • 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: Maria
Triple: [Johanna Maria Ruyter, givenName, Maria]
Generated description
Maria is a feminine given name of Latin origin, widely used across many cultures and often associated with Christian traditions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maria
Target entity description: Maria is a feminine given name of Latin origin, widely used across many cultures and often associated with Christian traditions.
  • A. Maria chosen
    Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
  • B. Maria
    Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
  • C. Maria
    Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
  • D. Maria
    Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
  • E. Maria
    Maria is the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
  • F. None of above.

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_69c68850419081909fb426b8f5a304c7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da8a65c48190b6862fc60f6c7f7a completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7586b6f0c8190a6caad7d020e9c4d completed March 28, 2026, 4:26 a.m.
NEDg Description generation batch_69c75a417b7481908846a53712ea2323 completed March 28, 2026, 4:34 a.m.
NED2 Entity disambiguation (via description) batch_69c75abf8de881908e1ae0a46da795bc completed March 28, 2026, 4:36 a.m.
Created at: March 27, 2026, 2:28 p.m.