Triple

T15716670
Position Surface form Disambiguated ID Type / Status
Subject Vasco Gonçalves E380977 entity
Predicate givenName P17 FINISHED
Object Vasco
Vasco is a masculine given name of Portuguese and Spanish origin, historically associated with explorers and notable figures from the Iberian Peninsula.
E1172737 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: Vasco | Statement: [Vasco Gonçalves, givenName, Vasco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasco
Context triple: [Vasco Gonçalves, givenName, Vasco]
  • A. Vasco
    Vasco is the internal codename for Nokia's N8 smartphone, a flagship Symbian device known for its advanced camera and multimedia capabilities.
  • B. Santos
    Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
  • C. Santos
    Santos is a major Australian oil and gas exploration and production company with significant operations across Australia and the Asia-Pacific region.
  • D. Santos
    Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
  • E. Portuguesa Santista
    Portuguesa Santista is a Brazilian football club based in Santos, São Paulo, known for its youth development and regional tradition.
  • 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: Vasco
Triple: [Vasco Gonçalves, givenName, Vasco]
Generated description
Vasco is a masculine given name of Portuguese and Spanish origin, historically associated with explorers and notable figures from the Iberian Peninsula.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vasco
Target entity description: Vasco is a masculine given name of Portuguese and Spanish origin, historically associated with explorers and notable figures from the Iberian Peninsula.
  • A. Vasco
    Vasco is the internal codename for Nokia's N8 smartphone, a flagship Symbian device known for its advanced camera and multimedia capabilities.
  • B. Santos
    Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
  • C. Santos
    Santos is a major Australian oil and gas exploration and production company with significant operations across Australia and the Asia-Pacific region.
  • D. Santos
    Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
  • E. Portuguesa Santista
    Portuguesa Santista is a Brazilian football club based in Santos, São Paulo, known for its youth development and regional tradition.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f91beb08190bd91bf9306737c3b completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7583609c8190a80421fce649900f completed May 9, 2026, 5:57 p.m.
NEDg Description generation batch_69ff76deb1948190bc49825719ac97d5 completed May 9, 2026, 6:03 p.m.
NED2 Entity disambiguation (via description) batch_69ff77642ba4819095c1acc65da06135 completed May 9, 2026, 6:05 p.m.
Created at: April 10, 2026, 4:45 a.m.