Triple

T4544044
Position Surface form Disambiguated ID Type / Status
Subject Daniel E110004 entity
Predicate hasFeminineForm P1613 FINISHED
Object Daniela
Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
 E451928 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: Daniela | Statement: [Daniel, hasFeminineForm, Daniela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daniela
Context triple: [Daniel, hasFeminineForm, Daniela]
  • A. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • B. Renata
    Renata is a vampire in the Twilight series who serves the Volturi as a powerful bodyguard with a psychic ability to repel physical attacks.
  • C. Renata
    Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • 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: Daniela
Triple: [Daniel, hasFeminineForm, Daniela]
Generated description
Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daniela
Target entity description: Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
  • A. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • B. Renata
    Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
  • C. Renata
    Renata is a vampire in the Twilight series who serves the Volturi as a powerful bodyguard with a psychic ability to repel physical attacks.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57d517e881909c3d23ed4453b0a7 completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb936f3348190af0784d472bff312 completed March 20, 2026, 9:16 p.m.
NEDg Description generation batch_69bdbeb14e6881908c2a95dbe6b200e6 completed March 20, 2026, 9:40 p.m.
NED2 Entity disambiguation (via description) batch_69bdbf09a5f8819093f5f4ab483332b9 completed March 20, 2026, 9:41 p.m.
Created at: March 20, 2026, 1:05 p.m.