Triple

T8171966
Position Surface form Disambiguated ID Type / Status
Subject Carl Viggo Lange E190842 entity
Predicate givenName P17 FINISHED
Object Viggo
Viggo is a masculine given name of Scandinavian origin, commonly used in countries such as Denmark and Norway.
 E344797 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: Viggo | Statement: [Carl Viggo Lange, givenName, Viggo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Viggo
Context triple: [Carl Viggo Lange, givenName, Viggo]
  • A. Eric Northman
    Eric Northman is a centuries-old Viking vampire and charismatic bar owner who serves as a powerful and morally complex figure in the television series True Blood.
  • B. Theron
    Theron is a surname of Greek origin that has been borne by various notable individuals, including actors, athletes, and public figures.
  • C. Skarsgård
    Skarsgård is a prominent Swedish acting family name associated with several internationally recognized film and television performers.
  • D. Duron
    Duron is a budget line of x86-compatible microprocessors developed by AMD as a cost-effective alternative to its Athlon series.
  • E. Sakshaug
    Sakshaug is a village in the municipality of Inderøy in Trøndelag county, Norway, known for its historic church and rural setting.
  • 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: Viggo
Triple: [Carl Viggo Lange, givenName, Viggo]
Generated description
Viggo is a masculine given name of Scandinavian origin, commonly used in countries such as Denmark and Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Viggo
Target entity description: Viggo is a masculine given name of Scandinavian origin, commonly used in countries such as Denmark and Norway.
  • A. Eric Northman
    Eric Northman is a centuries-old Viking vampire and charismatic bar owner who serves as a powerful and morally complex figure in the television series True Blood.
  • B. Theron
    Theron is a surname of Greek origin that has been borne by various notable individuals, including actors, athletes, and public figures.
  • C. Skarsgård chosen
    Skarsgård is a prominent Swedish acting family name associated with several internationally recognized film and television performers.
  • D. Duron
    Duron is a budget line of x86-compatible microprocessors developed by AMD as a cost-effective alternative to its Athlon series.
  • E. Sakshaug
    Sakshaug is a village in the municipality of Inderøy in Trøndelag county, Norway, known for its historic church and rural setting.
  • F. None of above.

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_69ca82c1c0a08190bf8692b4d91a03ca completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4807c9808190ad91a9c688a4c7fd completed March 31, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf65ed508190abb60f9189f43e5c completed April 1, 2026, 6:47 a.m.
NEDg Description generation batch_69ccc312a8608190b899394752ef375f completed April 1, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ccd84893488190ae5376524650d5c4 completed April 1, 2026, 8:33 a.m.
Created at: March 30, 2026, 5:39 p.m.