Triple

T11397558
Position Surface form Disambiguated ID Type / Status
Subject Laka language E270016 entity
Predicate hasAlternativeName P39 FINISHED
Object Laka (Chad)
Laka (Chad) is a Central Sudanic language spoken primarily in southwestern Chad.
E923590 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: Laka (Chad) | Statement: [Laka language, hasAlternativeName, Laka (Chad)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laka (Chad)
Context triple: [Laka language, hasAlternativeName, Laka (Chad)]
  • A. Maba (Chad)
    Maba (Chad) is a Nilo-Saharan language spoken primarily by the Maba people in eastern Chad.
  • B. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • C. Koussassé
    Koussassé is an alternative name for the Kusaal language, a Gur language spoken primarily in northern Ghana and parts of Burkina Faso.
  • D. Sarh
    Sarh is a city in southern Chad that serves as a regional commercial and transportation hub along the Chari River.
  • E. Ndiass
    Ndiass is a village in western Senegal that serves as the host community for Blaise Diagne International Airport, one of the country’s main air transport hubs.
  • 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: Laka (Chad)
Triple: [Laka language, hasAlternativeName, Laka (Chad)]
Generated description
Laka (Chad) is a Central Sudanic language spoken primarily in southwestern Chad.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Laka (Chad)
Target entity description: Laka (Chad) is a Central Sudanic language spoken primarily in southwestern Chad.
  • A. Maba (Chad)
    Maba (Chad) is a Nilo-Saharan language spoken primarily by the Maba people in eastern Chad.
  • B. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • C. Koussassé
    Koussassé is an alternative name for the Kusaal language, a Gur language spoken primarily in northern Ghana and parts of Burkina Faso.
  • D. Sarh
    Sarh is a city in southern Chad that serves as a regional commercial and transportation hub along the Chari River.
  • E. Ndiass
    Ndiass is a village in western Senegal that serves as the host community for Blaise Diagne International Airport, one of the country’s main air transport hubs.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80019d3d48190a2f473deb6eae33a completed April 9, 2026, 7:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58cd74280819092f8c420630f4889 completed April 20, 2026, 2:17 a.m.
NEDg Description generation batch_69e59774e6648190a38b2515a83c2e0c completed April 20, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_69e5a3abf24481908fb71f4ef6b13532 completed April 20, 2026, 3:55 a.m.
Created at: April 8, 2026, 9:34 p.m.