Triple

T1169961
Position Surface form Disambiguated ID Type / Status
Subject Recife E24891 entity
Predicate hasPart P35 FINISHED
Object Madalena
Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
 E132979 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: Madalena | Statement: [Recife, hasPart, Madalena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Madalena
Context triple: [Recife, hasPart, Madalena]
  • A. 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.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Margarida
    Margarida is a given name, commonly used in Portuguese and Catalan, that corresponds to the English name Margaret.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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: Madalena
Triple: [Recife, hasPart, Madalena]
Generated description
Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Madalena
Target entity description: Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • A. 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.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • D. Margarida
    Margarida is a given name, commonly used in Portuguese and Catalan, that corresponds to the English name Margaret.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bce821b481908bc278a3fa7973f4 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66879aec819098293c440a0e09a6 completed March 7, 2026, 5:55 p.m.
NEDg Description generation batch_69ac66fd58308190bb4cb09581d4a8de completed March 7, 2026, 5:57 p.m.
NED2 Entity disambiguation (via description) batch_69ac677e147081909d9f64884c443f82 completed March 7, 2026, 5:59 p.m.
Created at: March 1, 2026, 7:45 p.m.