Triple

T3736951
Position Surface form Disambiguated ID Type / Status
Subject Gambian Muslims E79607 entity
Predicate language P15 FINISHED
Object Wolof E28117 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: Wolof | Statement: [Gambian Muslims, language, Wolof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolof
Context triple: [Gambian Muslims, language, Wolof]
  • A. Wolof chosen
    Wolof is a major Niger-Congo language spoken primarily in Senegal, The Gambia, and Mauritania, serving as a key lingua franca in the region.
  • B. Casamance Creole
    Casamance Creole is a Portuguese-based creole language spoken primarily in the Casamance region of Senegal, influenced by local West African languages.
  • C. 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.
  • D. Tamasheq
    Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
  • E. 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.
  • 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb3d32b081909a993a78b0869db8 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1e4cc48190bfc1078e9b06d2d9 completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:34 p.m.