Triple

T14500662
Position Surface form Disambiguated ID Type / Status
Subject Playa, Havana E359624 entity
Predicate contains P35 FINISHED
Object Sierra, Havana
Sierra is a neighborhood (barrio) within the Playa municipality of Havana, Cuba.
E1104371 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: Sierra, Havana | Statement: [Playa, Havana, contains, Sierra, Havana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sierra, Havana
Context triple: [Playa, Havana, contains, Sierra, Havana]
  • A. Santa Fe, Havana
    Santa Fe is a coastal neighborhood in the Playa municipality of Havana, Cuba, known for its seaside location and residential character.
  • B. City of Havana
    The City of Havana is the capital and largest city of Cuba, renowned for its historic architecture, vibrant cultural life, and significant political and economic role in the country.
  • C. Habana Goya
    Habana Goya is a graphics processing unit (GPU) architecture developed by Habana Labs, primarily designed to accelerate deep learning inference workloads in data centers.
  • D. Havana
    "Havana" is a Latin-influenced pop song by Cuban-American singer Camila Cabello that became an international hit and one of her signature tracks.
  • E. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • 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: Sierra, Havana
Triple: [Playa, Havana, contains, Sierra, Havana]
Generated description
Sierra is a neighborhood (barrio) within the Playa municipality of Havana, Cuba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sierra, Havana
Target entity description: Sierra is a neighborhood (barrio) within the Playa municipality of Havana, Cuba.
  • A. Santa Fe, Havana
    Santa Fe is a coastal neighborhood in the Playa municipality of Havana, Cuba, known for its seaside location and residential character.
  • B. City of Havana
    The City of Havana is the capital and largest city of Cuba, renowned for its historic architecture, vibrant cultural life, and significant political and economic role in the country.
  • C. Habana Goya
    Habana Goya is a graphics processing unit (GPU) architecture developed by Habana Labs, primarily designed to accelerate deep learning inference workloads in data centers.
  • D. Havana
    "Havana" is a Latin-influenced pop song by Cuban-American singer Camila Cabello that became an international hit and one of her signature tracks.
  • E. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de94dfe484819086dd971606e6478e completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
NEDg Description generation batch_69fd7b0160a08190ae181eb7acb3b6bc completed May 8, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_69fd7be778dc81908b0602bab944330a completed May 8, 2026, 6 a.m.
Created at: April 10, 2026, 1:21 a.m.