Triple
T12155624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pular |
E289566
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Guinean Fula
Guinean Fula is a regional variety of the Fula (Fulani) language spoken primarily in Guinea.
|
E963454
|
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: Guinean Fula | Statement: [Pular, alternativeName, Guinean Fula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guinean Fula Context triple: [Pular, alternativeName, Guinean Fula]
-
A.
Wolof
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.
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.
-
C.
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.
-
D.
Hausa-Fulani
Hausa-Fulani is a major ethnolinguistic group in West Africa, predominantly Muslim and influential in the politics, culture, and commerce of northern Nigeria and surrounding regions.
-
E.
Mandingo
Mandingo is a controversial 1975 American film set on a Southern slave plantation, known for its graphic depiction of slavery, racism, and sexual exploitation.
- 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: Guinean Fula Triple: [Pular, alternativeName, Guinean Fula]
Generated description
Guinean Fula is a regional variety of the Fula (Fulani) language spoken primarily in Guinea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guinean Fula Target entity description: Guinean Fula is a regional variety of the Fula (Fulani) language spoken primarily in Guinea.
-
A.
Wolof
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.
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.
-
C.
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.
-
D.
Hausa-Fulani
Hausa-Fulani is a major ethnolinguistic group in West Africa, predominantly Muslim and influential in the politics, culture, and commerce of northern Nigeria and surrounding regions.
-
E.
Mandingo
Mandingo is a controversial 1975 American film set on a Southern slave plantation, known for its graphic depiction of slavery, racism, and sexual exploitation.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c1673c8190830cd15525d16869 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69c8d408190abbc900deb534045 |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f5fe53d47c8190896a9abf8cc4bc31 |
completed | May 2, 2026, 1:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5ffc2cfd08190b87eccd3a73afc77 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 8, 2026, 9:50 p.m.