Triple

T14766184
Position Surface form Disambiguated ID Type / Status
Subject My Generation E347001 entity
Predicate basedOn P98 FINISHED
Object Onmoku (Swedish TV series)
Onmoku is a Swedish television series that served as the inspiration for the American drama series My Generation.
E1119086 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: Onmoku (Swedish TV series) | Statement: [My Generation, basedOn, Onmoku (Swedish TV series)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Onmoku (Swedish TV series)
Context triple: [My Generation, basedOn, Onmoku (Swedish TV series)]
  • A. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • B. Omyènè
    Omyènè is an alternative name for Myene, a Bantu language spoken primarily along the coast of Gabon.
  • C. Ommen
    Ommen is a small historic town and municipality in the Dutch province of Overijssel, known for its scenic river landscapes and tourism.
  • D. Ojakkala
    Ojakkala is a village in the municipality of Vihti in southern Finland, known for its rural residential character and proximity to the Helsinki metropolitan area.
  • E. Ô Môn
    Ô Môn is an urban district of Cần Thơ in Vietnam’s Mekong Delta, known for its agricultural activities and growing urban development.
  • 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: Onmoku (Swedish TV series)
Triple: [My Generation, basedOn, Onmoku (Swedish TV series)]
Generated description
Onmoku is a Swedish television series that served as the inspiration for the American drama series My Generation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Onmoku (Swedish TV series)
Target entity description: Onmoku is a Swedish television series that served as the inspiration for the American drama series My Generation.
  • A. Mo i Rana
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • B. Omyènè
    Omyènè is an alternative name for Myene, a Bantu language spoken primarily along the coast of Gabon.
  • C. Ommen
    Ommen is a small historic town and municipality in the Dutch province of Overijssel, known for its scenic river landscapes and tourism.
  • D. Ojakkala
    Ojakkala is a village in the municipality of Vihti in southern Finland, known for its rural residential character and proximity to the Helsinki metropolitan area.
  • E. Ô Môn
    Ô Môn is an urban district of Cần Thơ in Vietnam’s Mekong Delta, known for its agricultural activities and growing urban development.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f576c881909da70627f5897c94 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cf68d94819093567bc630f67b60 completed May 8, 2026, 4:19 p.m.
NEDg Description generation batch_69fe1b0056988190b14560470428d895 completed May 8, 2026, 5:18 p.m.
NED2 Entity disambiguation (via description) batch_69fe1b97e8148190b23a555b9f2c7f1f completed May 8, 2026, 5:21 p.m.
Created at: April 10, 2026, 1:30 a.m.