Triple

T5656226
Position Surface form Disambiguated ID Type / Status
Subject Julie E124624 entity
Predicate hasCognate P2525 FINISHED
Object Juliana (Spanish and Portuguese)
Juliana is a feminine given name common in Spanish and Portuguese-speaking countries, derived from the Latin name Julianus and related to names like Julia and Julie.
 E537687 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: Juliana (Spanish and Portuguese) | Statement: [Julie, hasCognate, Juliana (Spanish and Portuguese)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Juliana (Spanish and Portuguese)
Context triple: [Julie, hasCognate, Juliana (Spanish and Portuguese)]
  • A. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • B. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • C. María
    María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
  • D. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • E. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • 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: Juliana (Spanish and Portuguese)
Triple: [Julie, hasCognate, Juliana (Spanish and Portuguese)]
Generated description
Juliana is a feminine given name common in Spanish and Portuguese-speaking countries, derived from the Latin name Julianus and related to names like Julia and Julie.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Juliana (Spanish and Portuguese)
Target entity description: Juliana is a feminine given name common in Spanish and Portuguese-speaking countries, derived from the Latin name Julianus and related to names like Julia and Julie.
  • A. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • B. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • C. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • D. María
    María is the given first name of Josefa Ortiz de Domínguez, a prominent figure in Mexico’s War of Independence.
  • E. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • 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_69c0082774a481909d7e63fb2aad56ac completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022fb0b74819084782411bd172834 completed March 22, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d9ec1248190aff680acb4064a49 completed March 22, 2026, 8:14 p.m.
NEDg Description generation batch_69c04ede30088190a70607458f4653d0 completed March 22, 2026, 8:19 p.m.
NED2 Entity disambiguation (via description) batch_69c04fb365cc8190b825f7c1d66aee0f completed March 22, 2026, 8:23 p.m.
Created at: March 22, 2026, 3:42 p.m.