Triple

T10852558
Position Surface form Disambiguated ID Type / Status
Subject Vamma power station E256183 entity
Predicate hasDam P8736 FINISHED
Object Vamma dam
Vamma dam is a hydroelectric dam in Norway that impounds the Glomma River to supply water for the Vamma power station.
 E888871 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: Vamma dam | Statement: [Vamma power station, hasDam, Vamma dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vamma dam
Context triple: [Vamma power station, hasDam, Vamma dam]
  • A. Maamme
    Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
  • B. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • C. Muddonna
    Muddonna is the costumed female mascot of the Toledo Mud Hens minor league baseball team, known for entertaining fans at games and team events.
  • D. Missamma
    Missamma is a classic 1955 Telugu romantic comedy film, celebrated for its witty screenplay, memorable music, and iconic performances by Savithri and N. T. Rama Rao.
  • E. Les Muma
    Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
  • 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: Vamma dam
Triple: [Vamma power station, hasDam, Vamma dam]
Generated description
Vamma dam is a hydroelectric dam in Norway that impounds the Glomma River to supply water for the Vamma power station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vamma dam
Target entity description: Vamma dam is a hydroelectric dam in Norway that impounds the Glomma River to supply water for the Vamma power station.
  • A. Maamme
    Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
  • B. Menmaatre
    Menmaatre was the throne name of the ancient Egyptian pharaoh Seti I of the Nineteenth Dynasty.
  • C. Muddonna
    Muddonna is the costumed female mascot of the Toledo Mud Hens minor league baseball team, known for entertaining fans at games and team events.
  • D. Missamma
    Missamma is a classic 1955 Telugu romantic comedy film, celebrated for its witty screenplay, memorable music, and iconic performances by Savithri and N. T. Rama Rao.
  • E. Les Muma
    Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75134299481909459fd87917261a7 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb17d978c8190883b4a56e88859de completed April 14, 2026, 9:28 p.m.
NEDg Description generation batch_69deb515ab608190981689bcad4b7530 completed April 14, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69deb602fa908190bffdd291932da3f1 completed April 14, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:20 p.m.