Triple

T4443751
Position Surface form Disambiguated ID Type / Status
Subject Erlang E96230 entity
Predicate designedBy P184 FINISHED
Object Robert Virding
Robert Virding is a computer scientist best known as one of the original creators of the Erlang programming language.
 E442479 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: Robert Virding | Statement: [Erlang, designedBy, Robert Virding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Robert Virding
Context triple: [Erlang, designedBy, Robert Virding]
  • A. Rolf Nilsen
    Rolf Nilsen is a businessman best known as the owner of the Ontario Hockey League’s Flint Firebirds.
  • B. Erik Selvig
    Erik Selvig is a fictional astrophysicist in the Marvel Cinematic Universe who becomes a close ally of Thor and plays a key role in studying and understanding cosmic phenomena.
  • C. Jörgen Persson
    Jörgen Persson is a Swedish cinematographer known for his work on numerous acclaimed films, including the 1998 adaptation of Les Misérables.
  • D. Rolf Carls
    Rolf Carls was a high-ranking German naval officer and admiral who played a significant command role in the Kriegsmarine during the World Wars.
  • E. Ragnar Östberg
    Ragnar Östberg was a prominent Swedish architect best known for designing Stockholm City Hall and for his influential role in early 20th-century Nordic architecture.
  • 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: Robert Virding
Triple: [Erlang, designedBy, Robert Virding]
Generated description
Robert Virding is a computer scientist best known as one of the original creators of the Erlang programming language.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Robert Virding
Target entity description: Robert Virding is a computer scientist best known as one of the original creators of the Erlang programming language.
  • A. Rolf Nilsen
    Rolf Nilsen is a businessman best known as the owner of the Ontario Hockey League’s Flint Firebirds.
  • B. Erik Selvig
    Erik Selvig is a fictional astrophysicist in the Marvel Cinematic Universe who becomes a close ally of Thor and plays a key role in studying and understanding cosmic phenomena.
  • C. Jörgen Persson
    Jörgen Persson is a Swedish cinematographer known for his work on numerous acclaimed films, including the 1998 adaptation of Les Misérables.
  • D. Rolf Carls
    Rolf Carls was a high-ranking German naval officer and admiral who played a significant command role in the Kriegsmarine during the World Wars.
  • E. Ragnar Östberg
    Ragnar Östberg was a prominent Swedish architect best known for designing Stockholm City Hall and for his influential role in early 20th-century Nordic architecture.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355b052688190a0d8e5912f82151c completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b62818295481909c0ffa377570effc completed March 15, 2026, 3:31 a.m.
NEDg Description generation batch_69b628ffed1c819097d048712e9aafef completed March 15, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69b6298d1ff88190a58a6fc5992ef864 completed March 15, 2026, 3:37 a.m.
Created at: March 12, 2026, 11:32 p.m.