Triple

T13811099
Position Surface form Disambiguated ID Type / Status
Subject Puerto Plata E331889 entity
Predicate near P350 FINISHED
Object Sosúa
Sosúa is a coastal town in the Dominican Republic known for its beaches, tourism, and historical Jewish refugee community.
E1062170 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: Sosúa | Statement: [Puerto Plata, near, Sosúa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sosúa
Context triple: [Puerto Plata, near, Sosúa]
  • A. Cosío
    Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
  • B. Nalón
    The Nalón is a major river in Asturias, northern Spain, known for flowing through mountainous landscapes and historically supporting regional industry and mining.
  • C. Rabassa
    Rabassa is a surname most notably associated with Gregory Rabassa, the acclaimed American translator of Latin American literature.
  • D. Ocaña
    Ocaña is a historic city in northeastern Colombia known for its colonial architecture and role in the country’s independence-era events.
  • E. Ocaña
    Ocaña is a historic town in central Spain known for its large Plaza Mayor and its role as a regional cultural and commercial center.
  • 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: Sosúa
Triple: [Puerto Plata, near, Sosúa]
Generated description
Sosúa is a coastal town in the Dominican Republic known for its beaches, tourism, and historical Jewish refugee community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sosúa
Target entity description: Sosúa is a coastal town in the Dominican Republic known for its beaches, tourism, and historical Jewish refugee community.
  • A. Cosío
    Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
  • B. Nalón
    The Nalón is a major river in Asturias, northern Spain, known for flowing through mountainous landscapes and historically supporting regional industry and mining.
  • C. Rabassa
    Rabassa is a surname most notably associated with Gregory Rabassa, the acclaimed American translator of Latin American literature.
  • D. Ocaña
    Ocaña is a historic city in northeastern Colombia known for its colonial architecture and role in the country’s independence-era events.
  • E. Ocaña
    Ocaña is a historic town in central Spain known for its large Plaza Mayor and its role as a regional cultural and commercial center.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026ff6b481908066d6bf27064417 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b09161108190abbd97a30af9ab49 completed May 3, 2026, 8:31 p.m.
NEDg Description generation batch_69f7b138fda88190b2b7ffb51ce02a40 completed May 3, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7b28ca218819097fc35042d3b278a completed May 3, 2026, 8:39 p.m.
Created at: April 9, 2026, 10:12 p.m.