Triple

T11578440
Position Surface form Disambiguated ID Type / Status
Subject Dogon languages E274563 entity
Predicate hasSubgroup P747 FINISHED
Object Donno So
Donno So is a Dogon language spoken in Mali, known for its distinctive tonal system and complex noun classification.
 E934552 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: Donno So | Statement: [Dogon languages, hasSubgroup, Donno So]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Donno So
Context triple: [Dogon languages, hasSubgroup, Donno So]
  • A. Gono
    Gono is a Zimbabwean surname most notably borne by Gideon Gono, the former governor of the Reserve Bank of Zimbabwe.
  • B. Sooley
    Sooley is a novel by John Grisham that follows a young South Sudanese basketball player whose extraordinary talent offers a path out of war-torn hardship.
  • C. Donen
    Donen is a surname most famously associated with Stanley Donen, the American film director and choreographer known for classic Hollywood musicals such as "Singin' in the Rain."
  • D. Dona
    Dona is the nickname of Augusta Victoria of Schleswig-Holstein, the last German Empress and Queen of Prussia as the wife of Kaiser Wilhelm II.
  • E. Dondaicha
    Dondaicha is a town in the Dhule district of Maharashtra, India, known regionally as a local commercial and agricultural center.
  • 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: Donno So
Triple: [Dogon languages, hasSubgroup, Donno So]
Generated description
Donno So is a Dogon language spoken in Mali, known for its distinctive tonal system and complex noun classification.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Donno So
Target entity description: Donno So is a Dogon language spoken in Mali, known for its distinctive tonal system and complex noun classification.
  • A. Gono
    Gono is a Zimbabwean surname most notably borne by Gideon Gono, the former governor of the Reserve Bank of Zimbabwe.
  • B. Sooley
    Sooley is a novel by John Grisham that follows a young South Sudanese basketball player whose extraordinary talent offers a path out of war-torn hardship.
  • C. Donen
    Donen is a surname most famously associated with Stanley Donen, the American film director and choreographer known for classic Hollywood musicals such as "Singin' in the Rain."
  • D. Dona
    Dona is the nickname of Augusta Victoria of Schleswig-Holstein, the last German Empress and Queen of Prussia as the wife of Kaiser Wilhelm II.
  • E. Dondaicha
    Dondaicha is a town in the Dhule district of Maharashtra, India, known regionally as a local commercial and agricultural center.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904b46288190890ecafd6ceb0c3d completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69e714080a60819095205355776c8637 completed April 21, 2026, 6:07 a.m.
NEDg Description generation batch_69e720f9a8588190aa766d2e1628207a completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e72315dda08190996aa84587c5fc80 completed April 21, 2026, 7:11 a.m.
Created at: April 8, 2026, 9:38 p.m.