Triple

T2361117
Position Surface form Disambiguated ID Type / Status
Subject Lower Franconia E47272 entity
Predicate hasRiver P165 FINISHED
Object Sinn
Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia region.
 E259689 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: Sinn | Statement: [Lower Franconia, hasRiver, Sinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sinn
Context triple: [Lower Franconia, hasRiver, Sinn]
  • A. Nil Sine Numine
    Nil Sine Numine is a Latin phrase meaning "Nothing without divine will" or "Nothing without the deity," expressing reliance on a higher power.
  • B. Sines
    Sines is a coastal town in Portugal known as the birthplace of the famed explorer Vasco da Gama.
  • C. The Sin
    The Sin is a landmark 1965 Egyptian drama film directed by Henry Barakat, renowned for its stark portrayal of rural poverty and oppression and for featuring one of Faten Hamama’s most powerful performances.
  • D. Shifnal
    Shifnal is a small market town in Shropshire, England, known for its historic buildings and proximity to Telford.
  • E. Heed
    Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
  • 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: Sinn
Triple: [Lower Franconia, hasRiver, Sinn]
Generated description
Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sinn
Target entity description: Sinn is a river in northern Bavaria, Germany, that flows through the Lower Franconia region.
  • A. Nil Sine Numine
    Nil Sine Numine is a Latin phrase meaning "Nothing without divine will" or "Nothing without the deity," expressing reliance on a higher power.
  • B. Sines
    Sines is a coastal town in Portugal known as the birthplace of the famed explorer Vasco da Gama.
  • C. The Sin
    The Sin is a landmark 1965 Egyptian drama film directed by Henry Barakat, renowned for its stark portrayal of rural poverty and oppression and for featuring one of Faten Hamama’s most powerful performances.
  • D. Shifnal
    Shifnal is a small market town in Shropshire, England, known for its historic buildings and proximity to Telford.
  • E. Heed
    Heed is the fiercely loyal yet conflicted protagonist of Toni Morrison’s novel "Love," whose lifelong bond and rivalry with her friend Christine drive much of the story’s emotional and thematic tension.
  • 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_69a88a1a4a6081908645b0f2914521ab completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc723c66481908a9b94991f651b3b completed March 7, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea88cf3308190bdb5aac38aded823 completed March 9, 2026, 11:01 a.m.
NEDg Description generation batch_69aea91ce164819091aa24b287f9fb8e completed March 9, 2026, 11:03 a.m.
NED2 Entity disambiguation (via description) batch_69aea999b864819084134c670e7c5d9c completed March 9, 2026, 11:06 a.m.
Created at: March 4, 2026, 7:55 p.m.