Triple

T15187780
Position Surface form Disambiguated ID Type / Status
Subject Verbandsgemeinde Rhein-Mosel E362921 entity
Predicate contains P35 FINISHED
Object Löf
Löf is a small winegrowing village and municipality on the Moselle River in Rhineland-Palatinate, western Germany.
E1142358 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: Löf | Statement: [Verbandsgemeinde Rhein-Mosel, contains, Löf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Löf
Context triple: [Verbandsgemeinde Rhein-Mosel, contains, Löf]
  • A. Lofn
    Lofn is a lesser-known Norse goddess associated with gentleness and the sanctioning of forbidden or difficult loves among the Aesir.
  • B. Lyov
    Lyov is a transliterated form of the Russian given name Lev, commonly associated with figures like the writer Leo (Lev) Tolstoy.
  • C. Lofsrud
    Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
  • D.
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • E. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • 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: Löf
Triple: [Verbandsgemeinde Rhein-Mosel, contains, Löf]
Generated description
Löf is a small winegrowing village and municipality on the Moselle River in Rhineland-Palatinate, western Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Löf
Target entity description: Löf is a small winegrowing village and municipality on the Moselle River in Rhineland-Palatinate, western Germany.
  • A. Lofn
    Lofn is a lesser-known Norse goddess associated with gentleness and the sanctioning of forbidden or difficult loves among the Aesir.
  • B. Lyov
    Lyov is a transliterated form of the Russian given name Lev, commonly associated with figures like the writer Leo (Lev) Tolstoy.
  • C. Lofsrud
    Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
  • D.
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • E. Lödöse
    Lödöse is a historic Swedish town that was one of the country’s earliest and most important medieval trading centers, located in the province of Västergötland.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067995fc8190b048f15086bd42f0 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec895b59c81908a09f8393a35aa13 completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec9ece2fc8190811e83185cdb4dfc completed May 9, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_69fecc58d7b0819082090b6205b77b16 completed May 9, 2026, 5:55 a.m.
Created at: April 10, 2026, 3:09 a.m.