Triple

T6193651
Position Surface form Disambiguated ID Type / Status
Subject Kristiansand E138455 entity
Predicate hasRiver P165 FINISHED
Object Otra
Otra is a major river in southern Norway that flows through the Agder region to the city of Kristiansand before emptying into the Skagerrak.
 E576227 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: Otra | Statement: [Kristiansand, hasRiver, Otra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Otra
Context triple: [Kristiansand, hasRiver, Otra]
  • A. La Sele
    La Sele is the popular nickname for Costa Rica’s national football team, known for its passionate fan base and memorable World Cup performances.
  • B. Echenique
    Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
  • C. Marga
    Marga is a feminine given name, commonly used as a short or diminutive form of names like Margarita or Margareta.
  • D. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • E. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • 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: Otra
Triple: [Kristiansand, hasRiver, Otra]
Generated description
Otra is a major river in southern Norway that flows through the Agder region to the city of Kristiansand before emptying into the Skagerrak.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Otra
Target entity description: Otra is a major river in southern Norway that flows through the Agder region to the city of Kristiansand before emptying into the Skagerrak.
  • A. La Sele
    La Sele is the popular nickname for Costa Rica’s national football team, known for its passionate fan base and memorable World Cup performances.
  • B. Echenique
    Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
  • C. Marga
    Marga is a feminine given name, commonly used as a short or diminutive form of names like Margarita or Margareta.
  • D. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • E. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062431ae88190a1bf6ca91f3dc690 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f1c162081909cf34e827f1bd7d7 completed March 23, 2026, 4:49 p.m.
NEDg Description generation batch_69c1be41b0c881909aff05430b23dc71 completed March 23, 2026, 10:27 p.m.
NED2 Entity disambiguation (via description) batch_69c1bf50f6b881909e23e95d6ff0fd4d completed March 23, 2026, 10:31 p.m.
Created at: March 22, 2026, 4:19 p.m.