Triple

T3039406
Position Surface form Disambiguated ID Type / Status
Subject Haketia E83088 entity
Predicate influencedBy P9 FINISHED
Object Berber languages E4254 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: Berber languages | Statement: [Haketia, influencedBy, Berber languages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berber languages
Context triple: [Haketia, influencedBy, Berber languages]
  • A. Berber languages chosen
    The Berber languages are a group of closely related Afroasiatic languages traditionally spoken by the Indigenous Amazigh peoples of North Africa, particularly in countries such as Morocco, Algeria, Libya, and Tunisia.
  • B. Saharan languages
    Saharan languages are a branch of the Nilo-Saharan language family spoken mainly across the central Sahara and Sahel regions of Africa.
  • C. Riffian Berber
    Riffian Berber is a Northern Berber language spoken primarily by the Riffian people in the Rif region of northern Morocco.
  • D. Amazigh
    Amazigh are the Indigenous Berber peoples of North Africa, known for their distinct languages, culture, and historical presence across the Maghreb and Sahara regions.
  • E. Tashelhit
    Tashelhit is a variety of the Amazigh (Berber) language family spoken primarily in southwestern Morocco.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b2fa52c8190a7860f762d5232ab completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1decc2e3c8190abdafb11632741a0 completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.