Triple

T13343519
Position Surface form Disambiguated ID Type / Status
Subject Cristina Banegas E317886 entity
Predicate givenName P17 FINISHED
Object Cristina
Cristina is a feminine given name commonly used in Spanish, Portuguese, and other Romance-language cultures.
E1034840 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: Cristina | Statement: [Cristina Banegas, givenName, Cristina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cristina
Context triple: [Cristina Banegas, givenName, Cristina]
  • A. Cristina
    Cristina is one of the two free-spirited American women at the center of Woody Allen’s romantic drama film "Vicky Cristina Barcelona."
  • B. Cristina
    Cristina is the wife of Brazilian basketball legend Oscar Schmidt.
  • C. Cristina
    Cristina is a fictional cardiothoracic surgeon from the television series "Grey's Anatomy," known for her ambition, skill, and emotionally complex personality.
  • D. Cristina
    Cristina is a poem by Robert Browning included in his collection "Dramatic Romances and Lyrics."
  • E. Cristina
    Cristina was an American singer and influential figure in the early 1980s New York no wave and downtown music scene, known for her ironic, avant-pop reinterpretations of classic songs.
  • 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: Cristina
Triple: [Cristina Banegas, givenName, Cristina]
Generated description
Cristina is a feminine given name commonly used in Spanish, Portuguese, and other Romance-language cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cristina
Target entity description: Cristina is a feminine given name commonly used in Spanish, Portuguese, and other Romance-language cultures.
  • A. Cristina chosen
    Cristina is an Italian given name commonly used for women, equivalent to the English name Christina.
  • B. Cristina
    Cristina is a Spanish infanta and member of the Spanish royal family, known as the daughter of former King Juan Carlos I and Queen Sofía.
  • C. Cristina
    Cristina was an American singer and influential figure in the early 1980s New York no wave and downtown music scene, known for her ironic, avant-pop reinterpretations of classic songs.
  • D. Cristina
    Cristina is the wife of Brazilian basketball legend Oscar Schmidt.
  • E. Cristina
    Cristina is a fictional cardiothoracic surgeon from the television series "Grey's Anatomy," known for her ambition, skill, and emotionally complex personality.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8839b48190b164414b418e756c completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f726738ea08190b0b7634b29f5d94e completed May 3, 2026, 10:41 a.m.
NEDg Description generation batch_69f7270bf9308190a3e9427ffce0e3ee completed May 3, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_69f727d063c4819084b4990a0d759f79 completed May 3, 2026, 10:47 a.m.
Created at: April 9, 2026, 9:31 p.m.