Triple

T6613488
Position Surface form Disambiguated ID Type / Status
Subject Madeira wine E149290 entity
Predicate hasQualityCategory P33477 FINISHED
Object Frasqueira
Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
E608452 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: Frasqueira | Statement: [Madeira wine, hasQualityCategory, Frasqueira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frasqueira
Context triple: [Madeira wine, hasQualityCategory, Frasqueira]
  • A. Fariña
    Fariña is the surname of American folk singer, songwriter, and activist Mimi Fariña, known for her musical work and social advocacy.
  • B. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • C. Cantarranas
    Cantarranas is a small, historic town in central Honduras known for its colorful street murals and traditional cultural festivals.
  • D. Campanhã
    Campanhã is a parish and district in the eastern part of Porto, Portugal, known as a major transport hub and gateway to the city.
  • E. Vernazobre
    Vernazobre is a river in southern France that serves as a tributary of the Orb.
  • 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: Frasqueira
Triple: [Madeira wine, hasQualityCategory, Frasqueira]
Generated description
Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Frasqueira
Target entity description: Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
  • A. Fariña
    Fariña is the surname of American folk singer, songwriter, and activist Mimi Fariña, known for her musical work and social advocacy.
  • B. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • C. Cantarranas
    Cantarranas is a small, historic town in central Honduras known for its colorful street murals and traditional cultural festivals.
  • D. Campanhã
    Campanhã is a parish and district in the eastern part of Porto, Portugal, known as a major transport hub and gateway to the city.
  • E. Vernazobre
    Vernazobre is a river in southern France that serves as a tributary of the Orb.
  • 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_69c687ebc680819094caf71faba2efe2 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6d0a262808190a33ac94374affde4 completed March 27, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eee61df88190b3772e4756670b8f completed March 27, 2026, 8:56 p.m.
NEDg Description generation batch_69c6f09ffdd481909418ae33d1683486 completed March 27, 2026, 9:03 p.m.
NED2 Entity disambiguation (via description) batch_69c6f159cbf08190a22d7488584b4580 completed March 27, 2026, 9:06 p.m.
Created at: March 27, 2026, 1:57 p.m.