Triple

T12872047
Position Surface form Disambiguated ID Type / Status
Subject Zagora E307873 entity
Predicate languageUsed P238 FINISHED
Object Tamazight E164210 NE FINISHED

How this triple was built (2 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: Tamazight | Statement: [Zagora, languageUsed, Tamazight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tamazight
Context triple: [Zagora, languageUsed, Tamazight]
  • A. Tamazight chosen
    Tamazight is a branch of the Berber (Amazigh) languages of North Africa, encompassing several closely related varieties spoken across countries such as Morocco and Algeria.
  • B. Insular Tamazight
    Insular Tamazight is the extinct Berber language once spoken by the indigenous Guanche people of the Canary Islands.
  • C. Tashelhit
    Tashelhit is a variety of the Amazigh (Berber) language family spoken primarily in southwestern Morocco.
  • D. Beni Snous Tamazight
    Beni Snous Tamazight is a Zenati Berber variety traditionally spoken by the Beni Snous community in northwestern Algeria near the Moroccan border.
  • E. Tamazgha
    Tamazgha is the name used by many Amazigh (Berber) people for the broader North African homeland where their communities and cultures are rooted.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970905784819091631161a9de98c5 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8ccee708190bb4caa604386e3a3 completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 5:38 p.m.