Triple

T3730518
Position Surface form Disambiguated ID Type / Status
Subject Mosotho E79048 entity
Predicate traditionalMusic P526 FINISHED
Object Famo
Famo is a traditional Basotho music genre known for its accordion-driven melodies, poetic lyrics, and strong cultural and social commentary in Lesotho and surrounding regions.
 E384838 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: Famo | Statement: [Mosotho, traditionalMusic, Famo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Famo
Context triple: [Mosotho, traditionalMusic, Famo]
  • A. FAMO
    FAMO was a German vehicle manufacturer best known for producing military half-tracks and armored vehicles for the Wehrmacht during World War II.
  • B. FAMET
    FAMET is the Spanish Army’s aviation branch responsible for operating and supporting its helicopter and air mobility units.
  • C. Fiquet
    Fiquet is a French surname most notably borne by Hortense Fiquet, the model and wife of painter Paul Cézanne.
  • D. Fonyód
    Fonyód is a Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, marinas, and panoramic views of the lake and surrounding hills.
  • E. Farris
    Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
  • 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: Famo
Triple: [Mosotho, traditionalMusic, Famo]
Generated description
Famo is a traditional Basotho music genre known for its accordion-driven melodies, poetic lyrics, and strong cultural and social commentary in Lesotho and surrounding regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Famo
Target entity description: Famo is a traditional Basotho music genre known for its accordion-driven melodies, poetic lyrics, and strong cultural and social commentary in Lesotho and surrounding regions.
  • A. FAMO
    FAMO was a German vehicle manufacturer best known for producing military half-tracks and armored vehicles for the Wehrmacht during World War II.
  • B. FAMET
    FAMET is the Spanish Army’s aviation branch responsible for operating and supporting its helicopter and air mobility units.
  • C. Fiquet
    Fiquet is a French surname most notably borne by Hortense Fiquet, the model and wife of painter Paul Cézanne.
  • D. Fonyód
    Fonyód is a Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, marinas, and panoramic views of the lake and surrounding hills.
  • E. Farris
    Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
  • 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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb1bb5408190990ea4dfbdab5c68 completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db167c5881909772cf1e78717995 completed March 14, 2026, 3:50 a.m.
NEDg Description generation batch_69b4dc41a54c819099081242687e9011 completed March 14, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_69b4dcb9235c8190af2b5a5d222e8413 completed March 14, 2026, 3:57 a.m.
Created at: March 8, 2026, 3:34 p.m.