Triple

T11827503
Position Surface form Disambiguated ID Type / Status
Subject Senufo languages E281293 entity
Predicate hasMember P10 FINISHED
Object Nyarafolo language
The Nyarafolo language is a Senufo language spoken primarily in northern Côte d'Ivoire by the Nyarafolo people.
 E949734 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: Nyarafolo language | Statement: [Senufo languages, hasMember, Nyarafolo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nyarafolo language
Context triple: [Senufo languages, hasMember, Nyarafolo language]
  • A. Nyindrou language
    The Nyindrou language is an Oceanic language spoken by communities in the Admiralty Islands of Papua New Guinea.
  • B. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • C. Nyaturu language
    The Nyaturu language is a Bantu language spoken primarily by the Nyaturu people in central Tanzania.
  • D. Nyagbo language
    The Nyagbo language is a Niger-Congo language spoken by the Nyagbo people in the Volta Region of Ghana, closely related to other Ghana–Togo Mountain languages.
  • E. Nyaneka language
    The Nyaneka language is a Bantu language spoken primarily by the Nyaneka people of southwestern Angola.
  • 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: Nyarafolo language
Triple: [Senufo languages, hasMember, Nyarafolo language]
Generated description
The Nyarafolo language is a Senufo language spoken primarily in northern Côte d'Ivoire by the Nyarafolo people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nyarafolo language
Target entity description: The Nyarafolo language is a Senufo language spoken primarily in northern Côte d'Ivoire by the Nyarafolo people.
  • A. Nyindrou language
    The Nyindrou language is an Oceanic language spoken by communities in the Admiralty Islands of Papua New Guinea.
  • B. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • C. Nyaturu language
    The Nyaturu language is a Bantu language spoken primarily by the Nyaturu people in central Tanzania.
  • D. Nyagbo language
    The Nyagbo language is a Niger-Congo language spoken by the Nyagbo people in the Volta Region of Ghana, closely related to other Ghana–Togo Mountain languages.
  • E. Nyaneka language
    The Nyaneka language is a Bantu language spoken primarily by the Nyaneka people of southwestern Angola.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5ec3a148190bb184ba0d481b16a completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1671989f88190b8c1fb520435a25e completed April 29, 2026, 2:04 a.m.
NEDg Description generation batch_69f16e31ebfc81908255e24b96bf9a99 completed April 29, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_69f1a09eae7481908200709ae9721d53 completed April 29, 2026, 6:09 a.m.
Created at: April 8, 2026, 9:43 p.m.