Triple

T4837459
Position Surface form Disambiguated ID Type / Status
Subject Marija E108095 entity
Predicate relatedName P3889 FINISHED
Object Maria
Maria is a widely used female given name with roots in Hebrew and strong associations with Christian religious tradition.
 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: [Marija, relatedName, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maria
Context triple: [Marija, relatedName, 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: [Marija, relatedName, Maria]
Generated description
Maria is a widely used female given name with roots in Hebrew and strong associations with Christian religious tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maria
Target entity description: Maria is a widely used female given name with roots in Hebrew and strong associations with Christian religious tradition.
  • 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, originally named Maja Einstein, was Albert Einstein’s older sister, known for her close relationship with him and her work as a teacher and translator.
  • 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ce2e810819089f9a3f2a7574d44 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fa94f58819080b8b9c55fc604f9 completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be70c8e780819085662e7e62d2ad6b completed March 21, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_69be7139a288819087598a7da8c6ad42 completed March 21, 2026, 10:21 a.m.
Created at: March 20, 2026, 1:25 p.m.