Triple

T11114599
Position Surface form Disambiguated ID Type / Status
Subject Sinyar language E262851 entity
Predicate hasDialects P4251 FINISHED
Object Sinyar of Chad
Sinyar of Chad is a regional variety of the Sinyar language spoken by Sinyar communities within Chad.
E905165 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: Sinyar of Chad | Statement: [Sinyar language, hasDialects, Sinyar of Chad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinyar of Chad
Context triple: [Sinyar language, hasDialects, Sinyar of Chad]
  • A. Sinyar of Sudan
    Sinyar of Sudan is a dialectal variety of the Sinyar language spoken by the Sinyar people in parts of western Sudan.
  • B. Lakhdar
    Lakhdar is an Arabic masculine given name most notably borne by Algerian diplomat Lakhdar Brahimi.
  • C. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • D. Mai of Bornu
    Mai of Bornu was the royal title for the kings of the Bornu Empire in Central Africa, who ruled as powerful Islamic monarchs over the region for centuries.
  • E. Makouda
    Makouda is a town and commune located in northern Algeria within the Kabylie region.
  • 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: Sinyar of Chad
Triple: [Sinyar language, hasDialects, Sinyar of Chad]
Generated description
Sinyar of Chad is a regional variety of the Sinyar language spoken by Sinyar communities within Chad.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sinyar of Chad
Target entity description: Sinyar of Chad is a regional variety of the Sinyar language spoken by Sinyar communities within Chad.
  • A. Sinyar of Sudan chosen
    Sinyar of Sudan is a dialectal variety of the Sinyar language spoken by the Sinyar people in parts of western Sudan.
  • B. Lakhdar
    Lakhdar is an Arabic masculine given name most notably borne by Algerian diplomat Lakhdar Brahimi.
  • C. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • D. Mai of Bornu
    Mai of Bornu was the royal title for the kings of the Bornu Empire in Central Africa, who ruled as powerful Islamic monarchs over the region for centuries.
  • E. Makouda
    Makouda is a town and commune located in northern Algeria within the Kabylie region.
  • F. None of above.

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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79aa637888190935e852281408356 completed April 9, 2026, 12:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441cb16bc81908b5321506f655e38 completed April 19, 2026, 2:45 a.m.
NEDg Description generation batch_69e44c0606408190819b9d3fd58f818f completed April 19, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_69e4510dc55081908f89aab15726b2a8 completed April 19, 2026, 3:50 a.m.
Created at: April 8, 2026, 9:27 p.m.