Triple

T1765451
Position Surface form Disambiguated ID Type / Status
Subject Blue Men of the Sahara E38751 entity
Predicate language P15 FINISHED
Object Tamasheq
Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
E203666 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: Tamasheq | Statement: [Blue Men of the Sahara, language, Tamasheq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamasheq
Context triple: [Blue Men of the Sahara, language, Tamasheq]
  • A. Tashelhit
    Tashelhit is a variety of the Amazigh (Berber) language family spoken primarily in southwestern Morocco.
  • B. Badaga language
    Badaga language is a Southern Dravidian language spoken primarily by the Badaga community in the Nilgiri Hills of Tamil Nadu, India.
  • C. Kanuri
    The Kanuri are a major ethnic group of the central Sahara and Lake Chad region, historically associated with the Kanem-Bornu Empire and known for their distinct language and Islamic cultural heritage.
  • D. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • E. Dioula
    Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
  • 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: Tamasheq
Triple: [Blue Men of the Sahara, language, Tamasheq]
Generated description
Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tamasheq
Target entity description: Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
  • A. Tashelhit
    Tashelhit is a variety of the Amazigh (Berber) language family spoken primarily in southwestern Morocco.
  • B. Badaga language
    Badaga language is a Southern Dravidian language spoken primarily by the Badaga community in the Nilgiri Hills of Tamil Nadu, India.
  • C. Kanuri
    The Kanuri are a major ethnic group of the central Sahara and Lake Chad region, historically associated with the Kanem-Bornu Empire and known for their distinct language and Islamic cultural heritage.
  • D. Bambara
    Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
  • E. Dioula
    Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6467c3f08190abc8a06269ede908 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf4db1c48190a96f137db3e2f32c completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc0a3fdd88190b0ffa98db1b5cf80 completed March 8, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69adc12c894881909c9a82fc9e363a41 completed March 8, 2026, 6:34 p.m.
Created at: March 4, 2026, 7:31 p.m.