Triple
T2964538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pulaar |
E80128
|
entity |
| Predicate | hasLexicalInfluenceFrom |
P2268
|
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: [Pulaar, hasLexicalInfluenceFrom, Wolof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wolof Context triple: [Pulaar, hasLexicalInfluenceFrom, 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9958b1e48190a77f37bf63333c5b |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc9bc190819087cb35ee7c78825a |
completed | March 11, 2026, 5:24 a.m. |
Created at: March 8, 2026, 2:58 p.m.