Triple

T5182981
Position Surface form Disambiguated ID Type / Status
Subject Love's Labour's Lost E116963 entity
Predicate mainCharacter P1183 FINISHED
Object 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."
E500718 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: [Love's Labour's Lost, mainCharacter, Maria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maria
Context triple: [Love's Labour's Lost, mainCharacter, Maria]
  • A. Maria
    Maria is a track on Rage Against the Machine’s 2000 album "The Battle of Los Angeles," known for its politically charged lyrics and aggressive rap metal sound.
  • B. 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.
  • 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 birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
  • E. Maria
    Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
  • 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: [Love's Labour's Lost, mainCharacter, Maria]
Generated description
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."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maria
Target entity description: 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."
  • A. Maria
    Maria is a witty and sharp-tongued gentlewoman in Olivia’s household in Shakespeare’s comedy "Twelfth Night," known for her clever schemes and playful manipulation of other characters.
  • 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 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 a central character in the film "An Ordinary Couple," whose personal viewpoint shapes how the story’s everyday relationship dynamics are experienced and understood.
  • E. 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.
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd799d50388190bf2b7dfdd90949e9 completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee0815d848190bacd5ec6a778d91e completed March 21, 2026, 6:16 p.m.
NEDg Description generation batch_69bee58e4c748190bc216bd68c70e863 completed March 21, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69bee631b5e081908da0d0ffed1ff6b3 completed March 21, 2026, 6:40 p.m.
Created at: March 20, 2026, 1:46 p.m.