Triple

T1340502
Position Surface form Disambiguated ID Type / Status
Subject Kwa languages E28451 entity
Predicate hasSubgroup P747 FINISHED
Object Akebu language
The Akebu language is a Niger-Congo language spoken primarily by the Akebu people in parts of Togo and Ghana.
 E159732 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: Akebu language | Statement: [Kwa languages, hasSubgroup, Akebu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Akebu language
Context triple: [Kwa languages, hasSubgroup, Akebu language]
  • A. Kaxabu language
    The Kaxabu language is an indigenous Formosan language of Taiwan spoken by the Kaxabu people and considered highly endangered.
  • B. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • C. Abé language
    The Abé language is a Niger-Congo language spoken primarily by the Abé people of Côte d’Ivoire.
  • D. Chimariko language
    The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
  • E. Akan language
    Akan is a Central Tano language of the Niger-Congo family spoken primarily in Ghana, where it serves as a major lingua franca and vehicle of Akan culture.
  • 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: Akebu language
Triple: [Kwa languages, hasSubgroup, Akebu language]
Generated description
The Akebu language is a Niger-Congo language spoken primarily by the Akebu people in parts of Togo and Ghana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Akebu language
Target entity description: The Akebu language is a Niger-Congo language spoken primarily by the Akebu people in parts of Togo and Ghana.
  • A. Kaxabu language
    The Kaxabu language is an indigenous Formosan language of Taiwan spoken by the Kaxabu people and considered highly endangered.
  • B. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • C. Abé language
    The Abé language is a Niger-Congo language spoken primarily by the Abé people of Côte d’Ivoire.
  • D. Chimariko language
    The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
  • E. Akan language
    Akan is a Central Tano language of the Niger-Congo family spoken primarily in Ghana, where it serves as a major lingua franca and vehicle of Akan culture.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c21490488190b4281a16c87677d1 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde12d0dc81908a09c0221b8db3f6 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acde7990b4819082a1bcb50215d4f1 completed March 8, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_69acdee2d71481908a735d5685693ca8 completed March 8, 2026, 2:28 a.m.
Created at: March 1, 2026, 7:56 p.m.