Triple

T13263975
Position Surface form Disambiguated ID Type / Status
Subject Emily E315868 entity
Predicate hasVariantForm P457 FINISHED
Object Emilia (Spanish form)
Emilia (Spanish form) is the Spanish feminine given name equivalent to Emily, commonly used in Spanish-speaking countries.
 E1030832 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: Emilia (Spanish form) | Statement: [Emily, hasVariantForm, Emilia (Spanish form)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emilia (Spanish form)
Context triple: [Emily, hasVariantForm, Emilia (Spanish form)]
  • A. Emilia Gorriarán
    Emilia Gorriarán was the mother of Cuban revolutionary figure Camilo Cienfuegos.
  • B. Fabiola
    Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
  • C. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • 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. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • 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: Emilia (Spanish form)
Triple: [Emily, hasVariantForm, Emilia (Spanish form)]
Generated description
Emilia (Spanish form) is the Spanish feminine given name equivalent to Emily, commonly used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emilia (Spanish form)
Target entity description: Emilia (Spanish form) is the Spanish feminine given name equivalent to Emily, commonly used in Spanish-speaking countries.
  • A. Emilia Gorriarán
    Emilia Gorriarán was the mother of Cuban revolutionary figure Camilo Cienfuegos.
  • B. Fabiola
    Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
  • C. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • 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. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901c65048190bd8b3c4872f22520 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a48bc488190a5cf692d81bdcbba completed May 3, 2026, 8:41 a.m.
NEDg Description generation batch_69f70b5dbcc4819081b5ba410e319eb7 completed May 3, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_69f70c4c6f908190b2ebc2a90b049e59 completed May 3, 2026, 8:50 a.m.
Created at: April 9, 2026, 9:25 p.m.