Triple

T23329723
Position Surface form Disambiguated ID Type / Status
Subject Fernando Fitz-James Stuart, 17th Duke of Huéscar E591409 entity
Predicate givenName P17 FINISHED
Object Fernando
Fernando is a Spanish aristocrat who holds the title of 17th Duke of Huéscar in the House of Alba.
 E1579555 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: Fernando | Statement: [Fernando Fitz-James Stuart, 17th Duke of Huéscar, givenName, Fernando]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fernando
Context triple: [Fernando Fitz-James Stuart, 17th Duke of Huéscar, givenName, Fernando]
  • A. Fernando
    Fernando is the given name of Salgueiro Maia, a key Portuguese military officer who played a leading role in the Carnation Revolution.
  • B. Fernando
    Fernando was the given name of the Duke of Alba who served as governor-general, a prominent Spanish noble and military leader.
  • C. Fernando
    Fernando is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
  • D. Fernando
    Fernando is a fictional character portrayed by actor Jake T. Austin, likely in a television or film role.
  • E. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • 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: Fernando
Triple: [Fernando Fitz-James Stuart, 17th Duke of Huéscar, givenName, Fernando]
Generated description
Fernando is a Spanish aristocrat who holds the title of 17th Duke of Huéscar in the House of Alba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fernando
Target entity description: Fernando is a Spanish aristocrat who holds the title of 17th Duke of Huéscar in the House of Alba.
  • A. Fernando
    Fernando was the given name of the Duke of Alba who served as governor-general, a prominent Spanish noble and military leader.
  • B. Fernando
    Fernando is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
  • C. Fernando
    Fernando is a masculine given name of Spanish and Portuguese origin, commonly used in many Spanish-speaking and Lusophone countries.
  • D. Fernando
    Fernando is the given name of Salgueiro Maia, a key Portuguese military officer who played a leading role in the Carnation Revolution.
  • E. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • 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_69e25d1effe4819096907f95f610dbff completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197ec22a481908247f5f86acb6ab4 completed April 29, 2026, 5:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4cae1af88190a6e140a7e8b2ffd6 completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c4e669b6481909f198d1c51b68bf3 completed May 19, 2026, 11:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0c4f011a188190b801f2ae0f134356 completed May 19, 2026, 11:52 a.m.
Created at: April 17, 2026, 5:14 p.m.