Triple

T4542245
Position Surface form Disambiguated ID Type / Status
Subject Maria Nys E107560 entity
Predicate givenName P17 FINISHED
Object Maria
Maria is a feminine given name of Latin origin, widely used in 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: [Maria Nys, givenName, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maria
Context triple: [Maria Nys, givenName, Maria]
  • A. Maria
    Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
  • 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 the young Puerto Rican woman at the heart of the musical "West Side Story," whose forbidden romance with Tony drives the story’s modern retelling of "Romeo and Juliet."
  • D. Maria
    Maria is the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
  • E. Maria
    Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
  • 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: [Maria Nys, givenName, Maria]
Generated description
Maria is a feminine given name of Latin origin, widely used in 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 in 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 the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
  • E. Maria
    Maria was a late Roman noblewoman of the Western Roman Empire, known primarily as the daughter of the powerful general Stilicho and wife of Emperor Honorius.
  • 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_69bd43f922788190b7edfa294e39b178 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d3be988190bf118c4a87415613 completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb926f2608190bdc6379e81358c38 completed March 20, 2026, 9:16 p.m.
NEDg Description generation batch_69bdbe0b6aa88190b6e99e4be1b27935 completed March 20, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69bdbe5eda748190b6d83d5f2c73cff5 completed March 20, 2026, 9:38 p.m.
Created at: March 20, 2026, 1:04 p.m.