Triple

T1169971
Position Surface form Disambiguated ID Type / Status
Subject Recife E24891 entity
Predicate hasPart P35 FINISHED
Object Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
E135140 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: Tamarineira | Statement: [Recife, hasPart, Tamarineira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamarineira
Context triple: [Recife, hasPart, Tamarineira]
  • A. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • B. Panarima
    Panarima is a musical track featured on the album "Legend of the Sun Virgin."
  • C. Caicó
    Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
  • D. Alcântara
    Alcântara is a historic coastal municipality in the Brazilian state of Maranhão, known for its preserved colonial architecture and proximity to the Alcântara Launch Center.
  • E. Lapa
    Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • 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: Tamarineira
Triple: [Recife, hasPart, Tamarineira]
Generated description
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tamarineira
Target entity description: Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
  • A. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • B. Panarima
    Panarima is a musical track featured on the album "Legend of the Sun Virgin."
  • C. Caicó
    Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
  • D. Alcântara
    Alcântara is a historic coastal municipality in the Brazilian state of Maranhão, known for its preserved colonial architecture and proximity to the Alcântara Launch Center.
  • E. Lapa
    Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • 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_69ac6f17aa608190920b7df62b8dd903 completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac6fc5442c8190a5d824881f05d468 completed March 7, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_69ac7026dda48190a72f671dba9ac17b completed March 7, 2026, 6:36 p.m.
Created at: March 1, 2026, 7:45 p.m.