Triple

T8809280
Position Surface form Disambiguated ID Type / Status
Subject Kabiye E209614 entity
Predicate altName P39 FINISHED
Object Kabye
Kabye is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
 E759512 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: Kabye | Statement: [Kabiye, altName, Kabye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kabye
Context triple: [Kabiye, altName, Kabye]
  • A. Duékoué
    Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
  • B. Koné
    Koné is a principal town and administrative center on New Caledonia’s main island, Grande Terre.
  • C. Ziguinchor
    Ziguinchor is a major city in southern Senegal, serving as the regional capital of Casamance and an important cultural and economic hub.
  • D. Tenkodogo, Burkina Faso
    Tenkodogo is a historic town in eastern Burkina Faso, considered one of the country’s oldest settlements and an important regional center for the Gurma people.
  • E. Xala
    Xala is a 1974 satirical film (and earlier novel) by Ousmane Sembène that critiques post-independence African elites through the story of a corrupt businessman afflicted with impotence.
  • 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: Kabye
Triple: [Kabiye, altName, Kabye]
Generated description
Kabye is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kabye
Target entity description: Kabye is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
  • A. Duékoué
    Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
  • B. Koné
    Koné is a principal town and administrative center on New Caledonia’s main island, Grande Terre.
  • C. Ziguinchor
    Ziguinchor is a major city in southern Senegal, serving as the regional capital of Casamance and an important cultural and economic hub.
  • D. Tenkodogo, Burkina Faso
    Tenkodogo is a historic town in eastern Burkina Faso, considered one of the country’s oldest settlements and an important regional center for the Gurma people.
  • E. Xala
    Xala is a 1974 satirical film (and earlier novel) by Ousmane Sembène that critiques post-independence African elites through the story of a corrupt businessman afflicted with impotence.
  • 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_69ca8363f3308190a47e3f1ebd51f613 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fd4cbec8190a929d4e60da8ad65 completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6fa0e4308190bd01c2d107c8c02d completed April 3, 2026, 7:43 a.m.
NEDg Description generation batch_69cf718a6f2c81908f8b8d08a1437749 completed April 3, 2026, 7:51 a.m.
NED2 Entity disambiguation (via description) batch_69cf7275fea08190b8999fb30663ff17 completed April 3, 2026, 7:55 a.m.
Created at: March 30, 2026, 6:45 p.m.