Triple

T16986191
Position Surface form Disambiguated ID Type / Status
Subject San Miguel Department E412070 entity
Predicate contains P35 FINISHED
Object Carolina
Carolina is a locality in the San Miguel Department of El Salvador, known as a small town in the eastern part of the country.
 E1244328 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: Carolina | Statement: [San Miguel Department, contains, Carolina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Carolina
Context triple: [San Miguel Department, contains, Carolina]
  • A. Carolina
    Carolina is a common nickname for the University of North Carolina at Chapel Hill, a major public research university known for its strong academics and athletic programs.
  • B. Carolina
    Carolina is a feminine given name of Latin origin, commonly used in various languages as a form of Caroline or Charles.
  • C. Carolina
    "Carolina" is a country music album by American singer-songwriter Eric Church that helped establish his reputation for blending traditional country with rock influences.
  • D. Carolina
    Carolina is a small town in South Africa’s Mpumalanga province, known historically for coal mining and its rural, highveld surroundings.
  • E. Carolina
    Carolina was a major English colony in North America that later split into the separate colonies (and eventual U.S. states) of North Carolina and South Carolina.
  • 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: Carolina
Triple: [San Miguel Department, contains, Carolina]
Generated description
Carolina is a locality in the San Miguel Department of El Salvador, known as a small town in the eastern part of the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Carolina
Target entity description: Carolina is a locality in the San Miguel Department of El Salvador, known as a small town in the eastern part of the country.
  • A. Carolina
    Carolina is a small town in South Africa’s Mpumalanga province, known historically for coal mining and its rural, highveld surroundings.
  • B. Carolina
    Carolina is a major municipality in Puerto Rico, known for its urban character, commercial centers, and proximity to San Juan.
  • C. Carolina
    Carolina was a major English colony in North America that later split into the separate colonies (and eventual U.S. states) of North Carolina and South Carolina.
  • D. Carolina
    Carolina is a common nickname for the University of North Carolina at Chapel Hill, a major public research university known for its strong academics and athletic programs.
  • E. Carolina
    Carolina is a feminine given name of Latin origin, commonly used in various languages as a form of Caroline or Charles.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d27b58908190a643bcbd105b1849 completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1109a081908890bbd5958c76c2 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d5aeb0819086f1a5d279ac0d0f completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0115c583608190bf07ac205399f253 completed May 10, 2026, 11:33 p.m.
Created at: April 10, 2026, 5:32 a.m.